Search Results - EGA European Genome-Phenome Archive

Single_cell_measurements_to_characterise_B_cell_repopulation_in_SLE_after_rituximab_therapy__a_pilot_study

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease characterised by autoantibodies against DNA and nuclear proteins. Kidney involvement (lupus nephritis) is one of the most serious manifestations and is the leading determinant of long-term prognosis. Therapies targeting B cells (e.g. rituximab) are used in the treatment of severe lupus, including lupus nephritis. Rituximab is a monoclonal antibody that targets the CD20 surface protein on the surface of B cells. Following rituximab treatment, there is near complete depletion of B cells in peripheral blood. Peripheral blood B cells slowly return over a period of months. The speed of repopulation varies but typically B cells have returned to baseline levels between 9 and 12 months post rituximab therapy. Return of B cells may be associated with increased disease activity, but this is not always the case. For example, some patients remain in clinical remission for several years following one cycle of rituximab, despite B cell repopulation, whilst others relapse as soon as the B cell number reaches the normal range. The reasons for the different response remain unclear. The B cell subpopulations that return following B cell depleting therapy have been previously studied using flow cytometry but have never been characterised using single cell -omic technologies and thus no data on their molecular signatures are available. Previous studies have shown that naïve B cells were the predominant repopulating B-cells, indicating de novo production of B cells. Obtaining an integrated understanding of the molecular programs of these cells at the single cell level will enhance our ability to predict disease outcome, to identify patients with poorer B-cell drug responses, understand disease heterogeneity and design more effective B-cell targeted therapies approach.

Study EGAS00001006798

Jeju Genome Project DAC

This Data Access Committee (DAC) evaluates and manages access requests for large-scale genomic and phenotypic datasets generated as part of the Jeju Genome Project (JGP). The committee's mission is to facilitate responsible data sharing to advance precision medicine and population genetics. The DAC ensures that data access is granted only to bona fide researchers who agree to the terms of the Data Access Agreement (DAA) and whose proposed research is strictly consistent with the informed consent provided by the participants and the ethical guidelines of the project.

Dac EGAC50000000938

Characterizing the Neurobehavioral Phenotype(s) in MPS III (Pilot Study)

Mucopolysaccharidosis III (MPSIII) syndrome is characterized by a severe cognitive decline ending in dementia and death. MPSIII is also associated with a range of abnormal and disruptive behaviors that can include, but go well beyond, childhood noncompliance and oppositionality. The purpose of this study is to conduct a cross-sectional investigation to identify the behavioral phenotype and its neural basis in MPSIII. An overall goal of this research is to develop easily administered, sensitive and specific neurobehavioral markers to characterize the behavioral phenotype(s) of MPSIII, track their progression, and to delineate their possible neural substrates. The study looks to develop develop a sensitive and specific behavioral rating of disease progression in MPS III which can be used for clinical outcome studies. The research objectives are: Develop a measure for the use of health professionals to use in tracking MPSIII phenotypes and disease progression. Test our model of MPSIII with objectively recorded behaviors in a well-defined experimental setting. Elucidate the neural bases of MPSIII by correlating behavioral profiles with changes in brain structures through quantitative neuroimaging. Determine the relationship between the loss of cognitive functions and development of behavioral abnormalities in MPSIII. This is an observational pilot study that will enroll 45 individuals with MPS III Type A or B. Those participating in the study will be evaluated during a one-day assessment and chart review.

Study phs001330

Molecular Determinants of Tumor Behavior in Early Lung Adenocarcinoma

Lung adenocarcinoma is the leading cause of cancer death worldwide and a heterogeneous disease with poor survival in the advanced stage. Given that the frequency of early diagnosis is increasing, the investigation of the molecular determinants of disease progression is paramount. Prediction of whether the tumor is indolent or aggressive has been the subject of recent investigations. Yet, the molecular underpinnings explaining the difference in tumor behavior remains largely unknown and is directly relevant to the efficacy and cost-effectiveness of lung cancer screening, including the risks of over-diagnosis and overtreatment. To gain insights into the molecular pathogenesis and the underlying molecular determinants of clinical behavior of early adenocarcinoma, we investigated genetic alterations in 102 surgically resected early adenocarcinomas. We hypothesized that the behavior of early adenocarcinoma can be predicted based on genomic underpinnings. To identify the type of genomic alterations associated with resected indolent and aggressive early lung ADC, the DNA samples from 21 adenocarcinoma in situ (AIS), 27 minimally invasive adenocarcinoma (MIA) and 54 fully invasive adenocarcinoma were collected and subjected to a deep next generation sequencing, targeting a custom 347 cancer gene panel. Our study provides new insights into cancer genomic evolution, helps to elucidate the interplay of somatic mutation and the adaptation of clones, and brings new insights into the key distinction between indolent and aggressive tumor behavior.

Study phs001811

Similarity and diversity of the tumor microenvironment in multiple metastases: critical implications for overall and progression-free survival of high-grade serous ovarian cancer.

The tumor microenvironment is pivotal in influencing cancer progression and metastasis. Different cells co-exist with high spatial diversity within a patient, yet their combinatorial effects are poorly understood. We investigate the similarity of the tumor microenvironment of 192 local metastatic lesions in 61 ovarian cancer patients. An ecologically inspired measure of microenvironmental diversity derived from multiple metastasis sites is correlated with clinicopathological characteristics and prognostic outcome. We demonstrate a high accuracy of our automated analysis across multiple sites. A low level of similarity in microenvironmental composition is observed between ovary tumor and corresponding local metastases (stromal ratio r = 0.30, lymphocyte ratio r = 0.37). We identify a new measure of microenvironmental diversity derived from Shannon entropy that is highly predictive of poor overall (p = 0.002, HR = 3.18, 95% CI = 1.51-6.68) and progression-free survival (p = 0.0036, HR = 2.83, 95% CI = 1.41-5.7), independent of and stronger than clinical variables, subtype stratifications based on single cell types alone and number of sites. Although stromal influence in ovary tumors is known to have significant clinical implications, our findings reveal an even stronger impact orchestrated by diverse cell types. Quantitative histology-based measures can further enable objective selection of patients who are in urgent need of new therapeutic strategies such as combinatorial treatments targeting heterogeneous tumor microenvironment.

Study EGAS00001002065

Using_genetics_to_identify_cell_types_and_mechanisms_underlying_susceptibility_to_primary_sclerosing_cholangitis

Primary sclerosing cholangitis (PSC) is a T-cell mediated, chronic inflammatory condition of the biliary tree that is strongly associated with inflammatory bowel disease. Genome-wide association studies have identified 22 non-HLA genetic risk variants associated PSC. Identifying the genes impacted by these variants has proven difficult as the majority lie in non-coding regions of the genome. Knowledge of the genes and biological pathways these non-coding variants are perturbing is vital to understanding the disease biology. One means of assessing the impact of non-coding variants within disease associated loci upon genes is via colocalisation with eQTL. Many eQTL are cell-type specific, requiring the analysis of disease relevant cell types to detect colocalisation. We have collected PSC-relevant T-cell-subtypes from the peripheral blood of PSC patients via fluorescence activated cell sorting in preparation for RNA sequencing and mapping of eQTL. Samples were collected at the Norfolk and Norwich University Hopital, for which local ethical approval has been granted. Lysed cell samples will be transferred to WTSI and DNA/RNA will be extracted from lysed cell samples by T143 before genotyping (DNA) and custom library preparation and sequencing (RNA). This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001002643

Identifying genetic consequences of Epstein-Barr Virus transformation by comparing an individual’s genomic DNA with that of its lymphoblastoid cell line.

A detailed analysis of whole genomes can be now achieved with next generation sequencing. Epstein Barr Virus (EBV) transformation is a widely used strategy in clinical research to obtain an unlimited source of a subject’s DNA. Although the mechanism of transformation and immortalization by EBV is relatively well known at the transcriptional and proteomic level, the genetic consequences of EBV transformation are less well understood. A detailed analysis of the genetic alterations introduced by EBV transformation is highly relevant, as it will inform on the usefulness and limitations of this approach. We used whole genome sequencing to assess the genomic signature of a low-passage lymphoblastoid cell line (LCL). Specifically, we sequenced the full genome (40X) of an individual using DNA purified from fresh whole blood as well as DNA from his LCL. A total of 217.33 Gb of sequence were generated from the cell line and 238.95 Gb from the normal genomic DNA. We determined with high confidence that 99.2% of the genomes were identical, with no reproducible changes in structural variation (chromosomal rearrangements and copy number variations) or insertion/deletion polymorphisms (indels). Our results suggest that, at this level of resolution, the LCL is genetically indistinguishable from its genomic counterpart and therefore their use in clinical research is not likely to introduce a significant bias.

Study EGAS00001000323

Using_genetics_to_identify_cell_types_and_mechanisms_underlying_susceptibility_to_primary_sclerosing_cholangitis

Primary sclerosing cholangitis (PSC) is a T-cell mediated, chronic inflammatory condition of the biliary tree that is strongly associated with inflammatory bowel disease. Genome-wide association studies have identified 22 non-HLA genetic risk variants associated PSC. Identifying the genes impacted by these variants has proven difficult as the majority lie in non-coding regions of the genome. Knowledge of the genes and biological pathways these non-coding variants are perturbing is vital to understanding the disease biology. One means of assessing the impact of non-coding variants within disease associated loci upon genes is via colocalisation with eQTL. Many eQTL are cell-type specific, requiring the analysis of disease relevant cell types to detect colocalisation. We have collected PSC-relevant T-cell-subtypes from the peripheral blood of PSC patients via fluorescence activated cell sorting in preparation for RNA sequencing and mapping of eQTL. Samples were collected at the Norfolk and Norwich University Hopital, for which local ethical approval has been granted. Lysed cell samples will be transferred to WTSI and DNA/RNA will be extracted from lysed cell samples by T143 before genotyping (DNA) and custom library preparation and sequencing (RNA). This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001002642

GAW16 Framingham and Simulated Data

Important links to apply for individual-level data Genetic Analysis Workshop Instructions to Request Authorized Access Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Research Use Statement Questions regarding GAW16 should be directed to Vanessa Olmo at vanessa@business-endeavors.com. Problem 2: Description of the Framingham Heart Study In GAW16, we use data drawn from the Framingham Heart Study. The Framingham Heart Study — under the direction of National Heart, Lung, and Blood Institute; NHLBI — began in 1948 with the recruitment of adults from the town of Framingham, Massachusetts. At the time, little was known about the general causes of heart disease and stroke, but the death rates for cardiovascular disease (CVD) had been increasing steadily since the beginning of the 20th century and had become an American epidemic. The Framingham Heart Study is now conducted in collaboration with Boston University. The objective of the Framingham Heart Study was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Between 1948 and 1953 the researchers recruited 5,209 subjects (2,336 men and 2,873 women) between the ages of 29 and 62 from the town of Framingham, Massachusetts and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Subjects were recruited from lists of addresses recorded for the town. Two out of every three households were approached for participation in the study. While there was no intention to recruit families for family studies, the plan was to recruit all household members in the ages 30-60 within each house that was selected for study. Hence, many biologically related individuals were recruited, including 1644 spouse pairs. Since 1948, these participants have returned to the study every two years for a detailed medical history, physical examination, and laboratory tests. Now in 2008 at 60 years of follow up, there remain about 500 participants from this cohort. Between 1971 and 1975 the study enrolled a second-generation group — 5,124 of the original participants' children and the spouses of these children — to participate in similar examinations. 2,616 subjects are offspring of the original spouse pairs and 34 are stepchildren. A total of 898 offspring are children of cohort members where only one parent was a study participant and 1,576 are spouses of the offspring. The Offspring Cohort has been followed every four years through 2001 (except between Exams 1 and 2 with an intervening 8 years) using protocols similar to those used for study of the Original Cohort. Between 2002 and 2005 the study enrolled the third generation (Gen3) of the Framingham Heart Study - 4095 offspring of the second generation. None of their spouses were recruited. An additional 103 parents of this third generation, who were not recruited between 1971 and 1975, were also recruited at this time. The latter group is not included in the GAW16 data. With the recruitment of this third generation, the study has increasingly focused on genetic factors associated with the development of cardiovascular disease and its associated risk factors. To date, there is only one examination of this generation of participants. A description of the recruitment of this third generation and comparison with the earlier generations at their initial recruitment is presented in Splansky GL et al., 2007. Further information on the Study can be found at http://www.nhlbi.nih.gov/about/framingham/index.html. Genome-wide Dense SNP Scan in Framingham Heart Study Genetic studies did not begin in the FHS until the 1990s. In the late 1980s and through the 1990s DNA was extracted from blood samples of surviving FHS participants. In 2007, the FHS entered a new phase with the conduct of genotyping for the FHS SHARe (SNP Health Association Resource) project, for which dense SNP genotyping was performed using approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel) in 10,775 samples (some duplicates) from the three generations of subjects (including over 900 pedigrees). Affymetrix conducted all genotyping for the FHS SHARe project, using the 250K Sty, 250K Nsp, and the supplemental 50K platforms. Eighty-nine percent of the DNA samples were collected during the 1990s. To maximize the power of the study, we also extracted DNA from 1133 blood samples, drawn from subjects who had no DNA, to include in the SHARe project. These samples had been sitting in our refrigerators for some time, a few as far back as the 1970s. We refer to these DNA samples as the legacy samples. These samples had a higher failure rate in the genotyping process (40%) than the other eighty-nine percent (3%). Affymetrix invoked its own criteria for a sample to succeed in genotyping. All non-legacy samples must succeed on all three platforms, while legacy samples needed to pass on at least one platform. When a sample failed, additional attempts were made. Samples that repeatedly failed 2-4 times were called failures. Other samples failed due to issues of genotyped sex identification not matching our records or low SNP concordance among SNPs common across arrays or contamination. Eighty-nine percent of the legacy samples for which genotyping results are available passed all three platforms. The genotyping data from the 10,043 samples from 9354 subjects that passed the Affymetrix criteria were additionally checked for gender consistency and consistency with family structure, resulting in genotyping data for 9,274 participants in FHS SHARe. Genotype calls were made with the BRLMM algorithm. The SHARe database is housed at the National Center for Biotechnology Information database of genotypes and phenotypes (NCBI dbGaP) and contains all ~550,000 SNPs. This genome-wide dense SNP scan and a subset of phenotypes from the Framingham Heart Study are the focus of the Genetic Analysis Workshop 16. Further information on the specific variables in the Problem 2 dataset can be found by clicking on the Documents tab at the top of the page. Problem 3: Description of the Simulated Data Set The focus of this simulation is gene discovery in genome-wide association scans (GWAS). The Framingham Heart Study data set (distributed as "Problem 2") is the basis for the FHS* simulated data. The pedigree structures are derived from the data distributed for Problem 2, and we distribute an accompanying triplet file (triplet_sim) containing person ID, father ID, mother ID, to ensure the identical subjects, pedigrees, and singletons are used in the simulated data analysis. Consistent with standard practice, founders and singletons are designated as subjects with both fshare and mshare equal to zero (missing). The simulated data includes a total of 6,479 subjects with both phenotype and genotype data, in 942 pedigrees distributed among 3 generations and 188 singletons. Data inclusion is consistent with the subjects' consent for use by both for-profit and not-for-profit researchers. The genotypes for all Problem 3 replicates are fixed as measured and distributed for Problem 2 for both the genomewide scan and the additional candidate gene SNPs, for a total of approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel). Thus, to analyze the Problem 3 simulated data you also will need to download the Problem 2 genotypes. Note that there are slight discrepancies in counts between Problems 2 and 3 due to a change in consents between the two datasets. Several phenotypes that contribute to coronary heart disease (CHD) were simulated for all individuals with genotypes across three different time points, 10 years apart. All genotyped individuals have complete data; the effects of missing values can be investigated by user-specified missing value patterns. There are 200 longitudinal datasets created, based on the generating model, and each replication is found in a separate dataset. We suggest that if only one replication is to be analyzed, that it be replication 1 to enable more precise comparisons among analytical approaches. The 'shareid' will allow you to merge the simulated phenotype data with the Problem 2 genotype data, and reconstruction of the pedigrees using the distributed 'triplet_sim' file or for larger families' relationships with the triplet distributed with the Problem 2. The simulated data problem is further described in the associated readme file, and a data dictionary is provided defining all the variables. For disclosure of the generating model for these data, please contact Jean MacCluer at jean@sfbrgenetics.org.

Study phs000128

Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer

No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing.

Study EGAS50000000211

Next Generation Mendelian Genetics: Congenital Hyperinsulinism

The NHGRI Next Generation Mendelian Genetics project uses exome resequencing to identify variants in unsolved Mendelian diseases. Congenital Hyperinsulinism (CHI) is the most common cause of hypoglycemia in the newborn and it is due to mutations in 8 different genes (ABCC8, KCNJ11, GLUD1, GCK, HADH, SLC16A1, HNF4A and UCP2). It is a heterogeneous disease with variable onset (birth to adulthood) and a persistent, intermittent, or transient course with possible later conversion to non-autoimmune diabetes. Although mutations in the two subunits of the KATP channel (ABCC8 and KCNJ11) account for 50% of the cases, the other half is still genetically unexplained. CHI can be inherited in a dominant or recessive and can also present as a 'de novo' mutation. We became part of this study when we submitted 8 DNA samples for exome sequencing, from patients with CHI of Caucasian ancestry, which had no mutations identified in ABCC8 or KCNJ1, with the goal to identify new mutations in known genes or new mutations in new genes or genetic variants.

Study phs000539

Study of Tumor Recurrence Related to the Expression of the PAX3-FOXO1 Oncogenic Transcription Factor in Fusion-Positive Rhabdomyosarcoma

Alveolar rhabdomyosarcoma (ARMS) is a highly aggressive pediatric soft tissue cancer characterized by a recurrent 2;13 chromosome translocation. This translocation generates a PAX3-FOXO1 (P3F) fusion gene, which encodes a chimeric transcription factor with oncogenic activity. Using a human myoblast system that models targeted therapy directed against P3F, we demonstrated that the expression of the fibroblast growth factor 8 (FGF8), a direct transcriptional target of P3F, is necessary and sufficient for PAX3-FOXO1-independent tumor recurrence in addition to be required for the tumorigenic activity of primary tumors expressing P3F. In addition, we showed that FGF8 is expressed in human rhabdomyosarcoma cell lines that express P3F. We also demonstrated that FGF8 contributes to their proliferation and transformation in vitro, and is sufficient to maintain their oncogenicity after the loss of P3F expression. We suggest that targeting the expression of the PAX3-FOXO1 transcription factor can generate resistance and recommend that additional anticipated therapeutic approaches, such as targeting FGF8 pathway, may avoid this resistance mechanism.

Study phs002344

Analysis of Epigenomes and Genome Topology in Colorectal Cancer

When diagnosing cancer, pathologists use nuclear morphology as a hallmark of tumor cells, but the topological changes linked to alterations in the shape of the nucleus were poorly understood. To uncover the molecular changes that occur in the 3D structure of cancer genomes, we integrated topological maps for colon tumors and normal colon tissues with epigenetic, transcriptional, and imaging data. We characterized tumor-associated changes in chromatin loops, topologically associated domains (TADs), and large-scale compartments. We found that chromatin loop rewiring contributes to oncogenic gene expression programs. Whereas TAD structures are largely stable, the spatial partitioning of the open and closed genome compartments is compromised in tumors and is accompanied by hypomethylation and histone mark rearrangements. We also identified a compartment that is reorganized in tumors and is at the interface between the canonical A and B compartments. Similar changes were evident in non-malignant cells that had accumulated excessive cellular divisions. Our analyses suggest that these compartment changes repress stemness and invasion programs while inducing immunity genes, and they may therefore restrain malignant progression.

Study phs002288

Normal Pressure Hydrocephalus

Idiopathic normal pressure hydrocephalus (iNPH) is a neurological disorder of aging that is characterized by enlarged cerebral ventricles, gait difficulty, incontinence and dementia. It is a common disorder that occurs almost exclusively after the age of 60. About 1.3% of patients over the age of 65 and 9-14% of nursing home residents are thought to have iNPH. Unfortunately, more than 90% of these patients remain misdiagnosed or undiagnosed, in part because the symptoms of iNPH resemble the symptoms of other neurodegenerative diseases, and in part because many health care practitioners are unfamiliar with this disorder. The etiology of iNPH is not known. Scattered reports of familial cases of iNPH suggest a genetic origin, but the genes involved are unknown. To investigate this matter, we have used exome sequencing to look for genetic factors associated with iNPH. We find recurrent heterozygous mutations in 10 genes, nearly all of which show increased expression in the ciliated ventricular epithelium and/or choroid plexus. Many have previously been associated with the function of cilia. 

Study phs002296

This study explored and validated the clinical application of targeted NGS of circulating tumor DNA in identifying tumor-specific mutations and uncovering clinical actionable targets in a variety of solid tumors in large patient cohorts.

Cancer is a disease of genetic alterations. Comprehensive genetic diagnosis is needed to match each patient to appropriate cancer therapy. However, acquisition of representative tumor samples is invasive and often infeasible. Circulating tumor DNA (ctDNA) is a promising non-invasive biomarker for cancer mutational profiling. Here we implemented targeted next generation sequencing (NGS) with a customized pan-cancer gene panel on 605 clinical ctDNA samples in multiple cancer types. Overall, tumor-specific mutations were identified in 87% of ctDNA samples, with mutation spectra highly concordant with their matched tumor tissues. 71% of patients have at least one clinical actionable mutation with 76% of which have suggested drugs approved or in clinical trials. In particular, our study reveals a unique mutation spectrum in Chinese lung cancer patients, which could be used to guide treatment decision and monitor the appearance of drug-resistant mutations. Taken together, our study demonstrated the clinical utility of target NGS-based ctDNA mutational profiling to guide cancer treatment decision.

Study EGAS00001002251

Mapping the breast cancer metastatic cascade onto circulating tumour DNA using genetic and epigenetic clonal tracking

Circulating tumour DNA (ctDNA) allows tracking the evolution of human cancers at high resolution, overcoming many limitations of tissue biopsies. However, exploiting ctDNA to determine how a patient’s cancer is evolving in order to aid clinical decisions remains difficult. This is because ctDNA is a mix of fragmented alleles, and the contribution of different cancer cell subpopulations from distinct lesions to ctDNA remains largely unknown. Profiling of ctDNA almost invariably requires prior knowledge of what genomic alterations to track. Here we leverage on a rapid autopsy programme to demonstrate that unbiased genomic characterisation of several metastatic sites and concomitant ctDNA profiling at whole-genome resolution reveals the extent to which ctDNA is representative of widespread disease. We also present a ctDNA methylation profiling method that allows tracking evolutionary changes in the cancer cell population at single-molecule resolution without prior knowledge. These results have critical implications for the use of liquid biopsies to monitor cancer evolution in humans and potentially guide treatment.

Study EGAS00001004014

WES of adult intellectual disabilities with co-morbid psychiatric disorders (2019-08-07)

ost adults with intellectual disabilities (ID) do not undergo genetic diagnostic investigation as part of their clinical care and have 'missed the boat' with regard to the WES and WGS genetic testing that is now being provided for children with ID. There is a dramatically increased risk of psychistric disorders in adults with ID, e.g. the risk of psychoses is 10X higher than in the general population. It remains an open question as to how much of adult ID is genetic in origin and how similar the genetic forms of adult ID are to those being diagnosed in children, in part due to survivor bias. There is also the opportunity to identify adults with treatable forms of ID, of which over 80 have been described, thus improving their clinical management. Furthermore, analysis of medical records of adults with genetic forms of ID can help to characterise the 'natural history' of individual disorders, resulting in more accurate prognoses for diagnosed children and identifying opportunities for improved management and possibly therapeutic intervention (e.g. optimal anti-epileptic therapy). Here we propose to exome sequence (to ~50X coverage) 200 adults with ID and co-morbid psychiatric disorders. This cohort has previously been assayed with chromosomal microarrays (Wolfe et al 2017 EJHG, 25, 66-72) identifying a diagnostic yield of ~11% which is comparable to the CNV diagnostic yield in various child ID cohorts (10-15%). The authors observed no substantive biases in diagnostic yield between different psychiatric diagnostic classes. The WES data will be analysed using the diagnostic workflows developed in the DDD study to ensure comparability between child and adult ID datasets. This study is intended as a pilot study to demonstrate the value of WES in adults with ID. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-08-07.

Dataset EGAD00001005236

NHGRI Genome Integrity of iPSCs Study

The purpose of this study is to compare mutation load in induced pluripotent stem cells derived from skin fibroblasts.

Study phs001277

DNA methylation array study for 7 pairs of primary NSCLCs and distant metastases

This study is to compare DNA methylation profiles between primary NSCLCs and paired distant metastases.

Study EGAS00001004079

Kidney_tumour_DNA

This is a bulk DNA and RNA sequencing study of human renal tumours

Study EGAS00001002486

Single Cell Targeted Sequence Capture

This study is to ascertain whether it is feasible to extract single cell from a tumour, perform amplification, generate a library and sequence a targeted pulldown.

Dataset EGAD00001001450

EGAD00000000008

WTCCC1 project Type 1 Diabetes (T1D) samples

Dataset EGAD00000000008

NHLBI TOPMed: The Genetics and Epidemiology of Asthma in Barbados

Asthma is a complex disease where the interplay between genetic factors and environmental exposures influences susceptibility and disease prognosis. Asthmatics of African descent tend to have more severe asthma and more severe clinical symptoms than individuals of European ancestry. The baseline prevalence of asthma in Barbados is high (~20%), and from admixture analyses, we have determined that the proportion of African ancestry among Barbadian founders is similar to U.S. African Americans, rendering this a unique population to disentangle the genetic basis for asthma disparities among African ancestry populations in general. We therefore performed whole genome sequencing on 1,100 individuals from the Barbados Genetics of Asthma Study (BAGS), in order to generate additional discovery of rare and structural variants that may control risk to asthma.

Study phs001143

Transcriptomic Analysis of Pluripotent Stem Cell-Based Model of Human Amniogenesis

The amniotic epithelium is the innermost layer of the amniochorionic membrane that physically divides the maternal and fetal environments. Amniogenesis is initiated during implantation in humans. In implanting blastocysts, the pluripotent epiblast cells undergo apical-basal polarization to form a cyst with a central lumen, the future amniotic cavity. This event is followed by the fate transition of pluripotent epiblast cells at the uterine-proximal pole of the cyst to squamous amniotic ectoderm, forming a sharp boundary between amnion and pluripotent epiblast portions of the cyst. To enable mechanistic investigations into amnion fate progression, several in vitro models based on human pluripotent stem cells were recently developed. In this study, transcriptomic features of human pluripotent stem cell-derived amniogenesis models were examined.

Study phs002184

HuBMAP: A 3-D Tissue Map of the Human Lymphatic System

The major goal of the 3-D Tissue Map of the Human Lymphatic System is to use microscopic and biomolecular procedures to facilitate co-registration pipelines and common 3D reconstruction algorithms. Tissue collected from human spleen, thymus and lymph node will be spatially resolved at the single cell level both within and across individuals. The approach employed involves sequencing of transcriptomes of dissociated cells and mapping to histological sections using CO-Detection by indEXing (CODEX) and /or Imaging mass spectroscopy, two highly multiplexed methods employing antibody-tagged target epitopes. Additionally, light sheet fluorescent microscopy is used to provide a higher level context for structural localization on a larger volume. The molecular data provided by this project is obtained through single-cell RNA-seq.

Study phs002268

Genomic landscape of Ewing sarcoma (ICGC project)

The Ewing sarcoma project aims to sequence 100 complete genomes of cells of patients suffering from this disease. It is an initiative of great projection, since this is the second most common bone tumor in children and teenagers. The goal of the project is to establish the catalogue of somatic mutations that may cooperate with EWS-ETS fusion in the development of the tumor. The Ewing sarcoma project aims to perform 100 whole genome sequencing of germline and tumor DNA as well as at least 50 RNA-seq from tumors. Correlations between molecular profiles and clinical features will be established. The mutated genes will be further validated in a series of 500 Ewing sarcoma cases from our Tumor Bank.

Study EGAS00001000855

Fixation effects on variant-calling in a clinical resequencing panel

Formalin fixation is the standard method for preservation of tissue for diagnostic purposes, including pathological review and molecular assays. However, this method is known to cause artifacts that can affect the accuracy of molecular genetic tests. We assessed the applicability of alternative fixatives to determine whether these perform significantly better on next-generation sequencing assays, and whether adequate morphology is retained for primary diagnosis, in a prospective study using a clinical-grade laboratory-developed targeted resequencing assay. We examined and quantified several parameters relating to sequencing quality and variant-calling from tumor and normal colon epithelial tissues. We identify one alterative fixative, Sakura Universal Molecular Fixative that suppresses many formalin-related artifacts while retaining adequate morphology for pathological review.

Study EGAS00001003507

Mitochondrial DNA mutations contribute to autism and also to the characteristics of mitochondrial disorders present in patients with autism spectrum disorders

Intellectual disability (ID) is common among autism spectrum disorder (ASD) patients. Also, evidence from many fields of medicine has documented multiple non-CNS physiological abnormalities associated with ASD, suggesting that, in some individuals, ASD arises from systemic, rather than organ-specific abnormalities. Oxidative phosphorylation and mitochondrial dysfunction are frequently reported in ASD and ID and can be due to mitochondrial DNA mutations. Therefore, the objective of the study was to analyze the mitochondrial DNA of ID subjects with ASD (N=98) and without ASD (N=95) to identify putative pathogenic variants that could be associated with ID or ASD. The genome of reference used in this is study is NC_012920.1 (rCRS) (Homo sapiens mitochondrion).

Study EGAS00001002750

NOTCH1 fusion genes in pediatric T-cell lymphoblastic lymphoma hallmark a common high-risk subgroup with blood TARC levels as possible biomarker

T-cell lymphoblastic lymphoma (T-LBL) is a common pediatric malignancy accounting for approximately 20% of the non-Hodgkin lymphomas during childhood. Survival rates of T-LBL are ~80%, but outcome after relapse is dismal, with salvage rates reaching only ~15. Considering the extremely poor prognosis after relapse and absence of clinically relevant high-risk genetics, there is an urgent need for the identification of molecular risk factors and new prognostic biomarkers in T-LBL, as well as identification of new therapeutic strategies. In this study we present a novel entity of high-risk pediatric T-LBL patients characterized by previously unknown NOTCH1 gene fusions and highly elevated blood TARC levels

Study EGAS00001007703

scRNAseq of ARID1B+/+ (control) and ARID1B+/- human telencephalic organoids at D120

This dataset contains scRNAseq data of human telencephalic organoids, at day 120, from 4 different sequencing runs (libraries), as follows (please see cell line clone nomenclature in original publication): 1. Library 177136: Pat.2 ARID1B+/+ clone 2c (2 organoids, E11rep_1, E11rep_2), Pat.2 ARID1B+/- clone 2a (2 organoids: B002orig_1, B002orig_2) 2. Library 178119: Pat.2 ARID1B+/+ clone 2c (3 organoids: E11rep_1, E11rep_2, E11rep_3), Pat.2 ARID1B+/- clone 2a (3 organoids: B002orig_1, B002orig_2, B002orig_3) 3. Library 178120: Pat.2 ARID1B+/+ clone 2d (3 organoids: A3rep_1, A3rep_2, A3rep_3), Pat.2 ARID1B+/- clone 2b (3 organoids: B002_F7_1, B002_F7_2, B002_F7_3) 4. Library 184337: Pat.1 ARID1B+/- clone 1a (3 organoids: B001orig_1, B001orig_2, B001orig_3), HD.1 ARID1B+/+ clone 3a (3 organoids: 176_1, 176_2, 176_3), HD.1 ARID1B+/- clone 3b (3 organoids: F10_1, F10_2, F10_3)

Dataset EGAD50000000498

Clonal diversity analysis and inter/intra-organ heterogeneity in urothelial carcinoma under immunotherapy

We studied a unique autopsy case of metastatic urothelial carcinoma with both sensitivity and resistance to anti-PD-1 therapy. We performed multiregional analyses of 58 paired whole exome sequencing and RNA sequencing samples of 8 different bulk tumor masses, 8 matched whole genome sequencing samples to identify structural abnormalities of each mass. Furthermore, we performed 7 whole exome sequencing from metastatic urothelial carcinoma patients who received anti-PD-1 therapy.

Study JGAS000725

Interval whole-genome sequence (WGS) data

Whole-genome sequencing (WGS) genotype data generated as part of the Interval project. The data are reported, separately per chromosome, in variant call format (VCF). The genotypes are denoted in diploid format (for chrY the genotype 1 denoted as 1/1 and 0 denoted as 0/0). Note that multi-allelic variants are present in the data, but encoded to appear on separate, consecutive lines. The data are reported in following versions - unphased, phased, phased with imputation, sites only. Note: the unphased version has additional genotype information, while the phased versions only contain the genotypes.

Dataset EGAD00001008661

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC -- CA209-009

Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

Study EGAS00001004290

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC -- CA209-010

Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

Study EGAS00001004291

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC-- CA209-025

Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

Study EGAS00001004292

Sequence-Based Analysis of Human Breast Tumors

The goal of this study is to study gene expression patterns in tumors, normal tissues, and cell lines.

Study phs000676

Compound heterozygous variants in LAMC3 in association with posterior periventricular nodular heterotopia

Periventricular nodular heterotopia is a malformation of cortical development characterized by nodules of abnormally migrated neurons.

Study EGAS00001004793

Biological Determinants of Peritoneal Dialysis Outcomes

Peritoneal Dialysis (PD) is a technique for treating kidney failure where fluid is instilled into the body's peritoneal cavity. Fluid and solutes travel across the peritoneum, and this is critical to successful PD. Studies have shown that certain demographic and clinical variables explain a small part of the variability in baseline peritoneal solute transfer rate and water transfer function across the peritoneum. This study sought to identify the common genetic variants associated with the baseline peritoneal function in patients starting treatment with PD and change in function upon treatment with PD. This study has two specific aims: Aim 1: To identify and validate genetic loci that influence the peritoneal solute transfer rate (PSTR) at start of PD. Aim 2: To identify and validate genetic loci in pre-specified biologic pathways with change in peritoneal ultrafiltration capacity. This study incorporates data from participants' peritoneal solute transfer rate in their first ever peritoneal equilibrium test (PET) and changes in the transfer of water across the peritoneal membrane over time in a sub-group of participants, demographic information, and results from laboratory analysis of DNA, blood, and dialysate. This study comprises patient populations from pre-existing biorepositories in Europe, and prospectively enrolled participants in United States, Canada, United Kingdom, and Australia. Clinical data related to the participants' peritoneal solute transfer rate from their first ever Peritoneal Equilibrium Test (PET), demographic information, and change in ultrafiltration capacity over time, are correlated with various genetic markers of interest. For individuals enrolled prospectively, blood and dialysate were collected at the first study visit. Annually, subjects either underwent a PET as standard of care or perform an additional 4-hour dwell as part of the study. These subsequent measures were utilized to determine change in ultrafiltration capacity over time. Inclusion criteria included adults over the age of 20 who are able to provide consent and had a record of a PET within 6 months of starting PD. Subjects with missing outcome data and that did not pass genotyping QC were excluded. Genotyping was performed in two batches using the Illumina InfiniumOmni2-5-8v1-3_A1 array with 2,372,784 single nucleotide variants (SNVs) in the first batch (n=1957). The second genotyping batch (n=1053) was on the InfiniumOmni2-5-8v1-4_A1 array with 2,382,209 SNVs. Imputation was performed using the Michigan Imputation Server and the HRC1.1 genotype reference. The Institutional Review Board of the University of Washington has “dbGaP-certified” the consent forms used to enroll participants in Australia, Canada, and United States and the genotype-phenotype data from the participants (n=827) deposited in the public repository. Furthermore, it has been determined that under the EU-GDPR regulations, depositing data of participants enrolled in UK, Belgium, and Sweden (n=2,023) into dbGaP “serves no lawful purpose” as the consent form used for enrolling participants did not obtain explicit permission for depositing data in a public repository.

Study phs002996

National Institute on Aging (NIA) Long Life Family Study (LLFS)

The Long Life Family Study (LLFS) is an international collaborative study of the genetics and familial components of exceptional survival, longevity, and healthy aging. Families were recruited through elderly probands (generally in their 90s) who self-reported on the survival history of their parents and siblings, and on the basis of this information, families which showed clustering of exceptional survival were recruited. [Specifically, a Family Longevity Selection Score (FLOSS) ≥7 was required. The FLOSS measures the average excess Observed lifespan over that Expected based upon lifetables, while adding a bonus term for still-living individuals. Thus FLOSS is a useful tool for scoring and selecting families for inclusion in a research study of exceptional survival (Sebastiani et al., 2009, PMID: 19910380)]. Probands resided in the catchment areas of four Field Centers (Boston University, Columbia University, University of Pittsburgh, and University of Southern Denmark). Recruited family members were phenotyped through extensive in-home visits by teams of technicians who traveled all over the USA and Denmark. Blood assays were centrally processed at a Laboratory Core (University of Minnesota) and protocols were standardized, monitored and coordinated through a Data Management Coordinating Center (Washington University). We examined and extensively phenotyped in all major domains of healthy aging, 4,953 individuals in 539 families through comprehensive in-home visits. Of these, 4,815 gave dbGaP sharing permission and had sufficient quantity/quality of DNA for GWAS genotyping. This large collection of families, selected on the basis of clustering for exceptional survival, is a unique resource for the study of human longevity and healthy aging. We estimate that less than 1% of the Framingham Heart Study (FHS) families (a roughly random population family sample) would meet the minimal entrance criteria for exceptional survival required in the LLFS (Sebastiani et al., 2009, PMID: 19910380). Thus, the least exceptional LLFS families show more clustering for exceptional longevity than 99% of the FHS families. Although the LLFS pedigrees were selected on the basis of longevity per se in the upper generation (and the generation above that), the children's generation have significantly lower rates of many major diseases and have better healthy aging profiles for many disease phenotypes (Newman et al., 2011, PMID: 21258136). The participants had their first in-person visit between 2006 and 2009. After that visit, they were contacted annually by telephone to update vital status, medical history, and general health. Between 2014 and 2017, willing participants completed a second in-person visit. The second visit followed the same protocols and centralized training as the first visit. During the second visit, a portable carotid ultrasound exam was added. Again, participants were continuously contacted annually for telephone follow-up during the period of the second in-person visit and after that. Annual telephone follow-ups currently ongoing, and plans for a third in-person visit are in progress.

Study phs000397

arcOGEN_HumanCoreExome-12v1-1_subset_2

Subset 2 of osteoarthritis cases from the arcOGEN Consortium (http://www.arcogen.org.uk/) genotyped on HumanCoreExome-12v1-1 with consent for osteoarthritis studies only.

Dataset EGAD00010000924

CIRCLE-seq of PDO

CIRCLE-seq data of PDAC 1 patient-derived organoid (PDO) - Unmapped reads, libraries were sequenced using the Illumina NextSeq500 with the NextSeq 500/550 Mid Output Kit v2.5 (300 Cycles), generating around 10M paired end 150bp reads per sample

Dataset EGAD50000000281

Colorectal_organoids_and_tumoroids___pulldown

Targeted capture of cancer gene panel bait set in single cell derived organoids from colon tissue and colorectal cancer from 1 patient.

Study EGAS00001000869

10x Genomics Single Cell Gene Expression for SA1051AX1XB01452

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1051 passage 1

Dataset EGAD00001009124

10x Genomics Single Cell Gene Expression for SA1052DX1XB01519

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

Dataset EGAD00001009122

10x Genomics Single Cell Gene Expression for SA1050FX1XB01446

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

Dataset EGAD00001009125

10x Genomics Single Cell Gene Expression for SA1093CX1XB01917

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1093 passage 1

Dataset EGAD00001009129

10x Genomics Single Cell Gene Expression for SA1049AX1XB01417

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1049 passage 1

Dataset EGAD00001009121

10x Genomics Single Cell Gene Expression for SA1091AX1XB01790

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1091 passage 1

Dataset EGAD00001009130

10x Genomics Single Cell Gene Expression for SA1052BX1XB01516

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

Dataset EGAD00001009127

10x Genomics Single Cell Gene Expression for SA1096AX1XB02034

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1096 passage 1

Dataset EGAD00001009132

Breast Cancer Follow Up Series

This study's purpose is to use data generated in whole genome and exome Breast Cancer sequencing to target specific areas in multiple other Breast Cancer samples. These areas will then be subjected to PCR in multiple cases, tagged and then pool the resultant amplicons. These amplicons will then be sequenced on the Illumina GAII. This is hoped to show the prevalence of previous findings in multiple individuals in a high throughput method.

Study EGAS00001000002

Myocardial Infarction Genetics Exome Sequencing Consortium: German Heart Center in Munich

The Munich-MI study is a case-control cohort study recruited at the German Heart Center in Munich, Germany. It is focused on understanding the genetic contributors to early myocardial-infarction (MI) in the German population. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Illumina's ICE Capture reagent and sequencing was performed on an Illumina HiSeq 2000 or 2500.

Study phs000916

Mutational Landscape of MCPyV-Positive and MCPyV-Negative Merkel Cell Carcinomas

Merkel cell carcinoma (MCC) is an aggressive neuroendocrine carcinoma of the skin most commonly found on the sun-exposed skin of older Caucasian adults. Roughly one-third of patients with MCCs die of the disease; therefore, MCC is the most lethal skin cancer on a case-by-case basis. 49 cases were studied, and putative cancer driver gene mutations and tumor antigens in both MCPyV-negative and MCPyV-positive MCCs were identified.

Study phs002515

Study of Cutaneous Biology of Cutaneous T Cell Lymphoma

This study is designed to help us understand the biological factors that contribute to the development of Cutaneous T Cell Lymphoma (CTCL) through the use of single-cell -omics technologies. The data that will be available include single-cell RNAseq and paired single-cell TCRseq data from the primary lesions of CTCL patients.The number of consented subjects listed here is artificially inflated by one to account for the pooling of all subjects.

Study phs002717

Whole-exome sequencing profiling of patients with metastatic prostate cancer at VHIO

Metastatic prostate cancer (mPC) is enriched for homologous recombination repair (HRR) gene alterations, which have prognostic and predictive value. Routine clinical implementation of next-generation sequencing (NGS) is still limited. We investigated the association between genomic and functional loss of HRR, using NGS and a RAD51 immunofluorescence (RAD51-IF) iprimary or metastatic biopsies from patients with stage IV prostate cancer. Whole-exome sequencing was pursued for paired tumor-normal samples.

Study EGAS50000000736

MOSAIC - Multi-Omics Spatial Atlas In Cancer

MOSAIC is a collaborative initiative founded by Owkin, Lausanne University Hospital (CHUV), Charité Universitätsmedizin Berlin, University Hospital Erlangen (UKER), Gustave Roussy Institute in Paris, and University of Pittsburgh. The goal of MOSAIC is to build the largest collection of spatial omics data in cancer. By integrating comprehensive high quality clinical annotations with advanced deep profiling techniques, MOSAIC aims to uncover novel cancer subtypes and identify key drug targets and biomarkers within them.

Study EGAS50000000689

Genomic landscape of poorly differentiated thyroid carcinoma

Poorly differentiated thyroid carcinoma (PDTC) is a rare and aggressive subtype of thyroid cancer with limited molecular characterization. This study aims to define the somatic mutational landscape of PDTC using whole-genome sequencing. Paired tumour and matched normal blood samples were collected from six patients undergoing surgery. The overarching goal is to identify recurrent mutations, structural variants, and other genomic alterations associated with tumour aggressiveness and poor clinical outcomes.

Study EGAS50000001134

RNAseq of medulloblastoma data (MB_COMICS cohort)

Medulloblastoma (MB) is the most common malignant brain tumor in children. It is a neuroectodermal tumor located in the cerebellum. International consensus recognizes four distinct subgroups of MBs including Wingless (WNT), Sonic Hedgehog (SHH), Group 3 (G3), and Group 4 (G4) with distinct molecular characteristics, prognoses, and mortality rates in patients. Here, we have compiled and evaluated a large international MB cohort for which we generated transcriptomic data (RNAseq) for 208 primary MB patient samples.

Study EGAS50000000410

OTOF mutation analysis with massively parallel DNA sequencing in 2,265 Japanese sensorineural hearing loss patients.

The OTOF gene, encoding otoferlin, is reported to be one of the major causes of non-syndromic recessive sensorineural hearing loss, and is also reported to be the most common cause of non-syndromic recessive auditory neuropathy spectrum disorder (ANSD). In the present study, we performed OTOF mutation analysis using massively parallel DNA sequencing (MPS) to reveal the frequency and clinical characteristics of OTOF-related hearing loss in a large hearing loss population.

Study JGAS000166

Analytical study of protein function and RNA expression involved in predicting treatment efficacy and adverse event development in lung cancer radiotherapy.

The purpose of this study is to elucidate the functions of DNA repair proteins and RNA expression that are involved in the therapeutic efficacy and adverse events of radiotherapy for lung cancer at our hospital. In particular, this is an exploratory study to identify proteins and RNAs involved in the expression of proteins that are likely to be involved in the prediction of radiotherapy response and adverse events.

Study JGAS000545

Development of blood-based biomarkers for precision medicine in castration-resistant prostate cancer

Cell-free DNA (cfDNA) testing is emerging as a tool for cancer precision medicine. However, little is known about the clinical significance of low-frequency variants detected in circulating cell-free tumor DNA (ctDNA) from castration-resistant prostate cancer (CRPC) patients. We conducted targeted sequencing of cfDNA and paired leukocyte DNA from CRPC patients using molecular barcodes, and ctDNA variants with a variant allele frequency ??? 0.1% were detected using an in-house pipeline.

Study JGAS000330

Deciphering the aggressive nature of morphoeic basal cell carcinoma

Morphoeic basal cell carcinoma (mBCC) has a high risk of local recurrence compared to the more indolent nodular subtype reflected by a different set of driver mutations including FLNB and HECTD4. Surrounding mBCC stroma is abnormal, containing mutations such as EPHA3. Hedgehog pathway over-expression is seen in both the tumour and stroma of morphoeic tissue with the latter potentially being partly responsible for its aggressive nature and risk of recurrence.

Study EGAS00001001915

IMMUcan Lung NSCLC2 cohort

The goal of IMMUcan is to understand how the immune system interacts with tumors and how therapeutic interventions influence this interaction. This cohort includes patients with non-small cell lung cancer who had surgical resection. This is a subcohort of the EORTC SPECTAlung study. Comprehensive profiling data are integrated with longitudinally collected clinical information. Cellular profiling of the same tumor samples was performed using multiplex immunofluorescence imaging, imaging mass cytometry, and H&E staining.

Study EGAS50000001558

Flexible and rapid validation of structural variants using adaptive sampling

The goal of the study is to confirm and further characterize structural variants and complex genomic rearrangements using adaptive sampling with Oxford Nanopore Sequencing. Individuals with known structural variants were included in the study and the known rearrangement regions were targeted in the sequencing experiments. In addition to long-read coverage over the targeted regions (around 25X coverage), the rest of the genome is covered by short off-target reads (around 5X coverage).

Study EGAS50000001279

Policy Documentation

Policy Documentation The following policy documentation is required to be prepared and submitted to the EGA, together with your data files and associated metadata. Data Access Agreement (DAA) The Data Access Agreement is a contract made between Data User and Data Access Committee. The agreement should be drafted by the DAC and includes, but is not limited to, details of data use, publication embargoes and storage. Completion of a DAA by the applicant/s should form part of the application process to the DAC. NOTICE The data access agreement template below is provided for guidance only and should be adapted as you see fit to suit your own purpose. In the interest of promoting data sharing, we suggest that if an agreement cannot be met around clause 19 in this example that both parties should agree to remain silent, and that the clause should be removed from the agreement. Example DAA template Alternate (harmonised) DAA template

Documentation access/data-access-committee/policy-documentation

Sequencing of heritable Bleeding and Platelet Disorders

The BRIDGE-BPD study aims to discover new causal genes for Bleeding and Platelet Disorders (BPD) by high throughput sequencing using cluster analyses based on improved and standardized deep phenotyping of cases. BPD is one of the 13 Rare Disease projects under the NIHR BioResource Rare Diseases BRIDGE consortium, which is a collaboration aiming to discover the genetic sequence variants underlying unresolved inherited disorders and to improve identification of already identified high penetrance variants.

Study EGAS00001001172

TRACERx 100: RNAseq data from the first 100 TRACERx tumours

TRACERx (TRAcking Cancer Evolution through therapy (Rx)) is a prospective cohort study designed to investigate intratumor heterogeneity (ITH) in relation to clinical outcome, and to determine the clonal nature of driver events and evolutionary processes in early stage non-small cell lung cancer (NSCLC). This study looks at the multi-region RNAseq data from the TRACERx100 cohort with high enough quality RNA available. There is RNAseq data from 164 regions (64 patients).

Study EGAS00001003458

Exome_sequencing_of_a_cohort_of_Rett_syndromelike_patients

The aim of the project is the definition of the molecular defect in a cohort of Rett-like patients negative for mutations in known disease genes. To this aim, a number of unrelated trios (patients plus parents) will be analysed by exome sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

Study EGAS00001002059

Sequencing of liver cancer cell lines

Liver cancer is a dreadful disease with limited therapeutic options. How to translate genomic findings into biomarkers and precision treatment is challenging. A large cell line-based platform was established, termed as Liver Cancer Model Repository. Heterogeneities in patients were faithfully recapitulated by 81 liver cancer cell lines at genomic and transcriptomic levels. This platform provides a rich resource and models to study cancer drivers and drug responses in liver cancer.

Study EGAS00001002237

Whole genome and RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

Paediatric glioblastoma (pedGBM) is characterised by substantial intertumoural heterogeneity. In order to identify the genetic lesions underlying tumourigenesis, we analysed whole genomes and transcriptomes of pedGBMs and in vitro model systems by next generation sequencing. Novel fusions of the receptor tyrosine kinase MET lead us to investigate targeted therapy using MET inhibitors. This study is part of the International Cancer Genome Consortium PedBrain Tumor Project (ICGC PedBrain, http://www.pedbraintumor.org/).

Study EGAS00001001139

Molecular subtypes of malignant peritoneal mesothelioma

Malignant Peritoneal Mesothelioma (PeM) is a rare but frequently fatal cancer that originates from the peritoneal lining of the abdomen. Standard treatment of PeM is limited to cytoreductive surgery and/or chemotherapy, and no targeted therapies for PeM yet exist. This study performs comprehensive integrative analysis of genome, transcriptome, and proteome of treatment-naive PeM tumors with the aim of identifying mesothelioma-related molecular alterations and potentially identifying novel treatment strategies.

Study EGAS00001002820

Whole genome sequencing of patients affected by acute intermittent porphyria

Acute intermittent porphyria (AIP) is an hereditary rare metabolic disorder of incomplete penetrance, affecting the biosynthesis of heme. IAP is an autosomal dominant disorder, resulting in a substantial reduction of the activity of the hydroxymethylbilane synthase coding gene (HMBS). Most HMBS mutation carriers are asymptomatic and only between 10% and 20% of patients present acute attacks of the associated symptoms. Here, we sequenced whole genomes of 16 AIP patients.

Study EGAS00001004999

glioblastoma single cell RNAseq

Understanding the cellular origin and differentiation status of glioblastoma is critical to resolve the etiology of the disease. we profile 18 patient glioblastomas by single cell RNA sequencing (scRNAseq). From this, we uncovered two principal cell-of-origin relations. Each lineage displays unique directional differentiation trajectories and transcriptional cores from the naïve cell populations. Thus, glioblastoma is defined by robust cell lineage features which may provide insights into the cell origin of the diseases.

Study EGAS00001006236

RNA sequencing of NK cells in human lung

Human lung tissue-resident NK cells (trNK cells) are likely to play important roles in viral infections, inflammation and cancer. However, knowledge about lung trNK cells is lacking but is fundamental for exploiting these cells in therapeutic approaches. Here we analysed the transcriptome of CD69+CD49a+CD103+CD16-CD56bright, CD69+CD49a+CD103-CD16-CD56bright, CD69+CD49a-CD103-CD16-CD56bright, CD69-CD49a-CD103-CD16-CD56bright, and CD56dimCD16+NKG2A+CD57- NK cells isolated from human lung.

Study EGAS00001003544

RNA sequencing in primary human macrophages overexpressing ETS2

We investigated an intergenic haplotype on chr21q22, linked to five different inflammatory diseases, and discovered a mechanism that orchestrates macrophage responses during chronic inflammation. We delineated how the risk haplotype increases expression of the causal gene, ETS2, and demonstrated that ETS2 is necessary for inflammatory macrophage effector functions. To establish whether ETS2 is sufficient to drive inflammatory responses, we overexpressed ETS2 in a dose-dependent manner and performed RNA-sequencing to characterise the transcriptional effects.

Study EGAS00001007554

The Gut Microbiome of liver transplant recipients – Cross-sectional + Longitudinal (renal and liver)

TransplantLines is designed as a single-center, prospective cohort study and biobank including all different types of solid organ transplant recipients as well as living organ donors. In the TransplantLines gut microbiome study the gut microbiome of solid organ transplant recipients is characterized and linked to clinical phenotypes. This batch contains the cross-sectional data from liver transplant recipients and longitudinal data from renal and liver transplant recipients.

Study EGAS00001006258

Changes in Oral and Gut Microbiota and Incidence and Severity of Patient-Reported Symptoms in Pre- and Post-Kidney Transplant Patients

This novel prospective cohort explores the relationships between oral and fecal microbiome features (alpha and beta diversity, differential relative abundances of bacterial taxa, and functional genes) and the incidence and severity of psychoneurological symptoms (e.g., pain, fatigue, depression, anxiety, and sleep disturbance) before and after patients receive a kidney transplant from a live donor. Thirty-five subjects provided fecal and saliva specimens for shotgun metagenomic sequencing of gut and oral microbiomes at 3 timepoints: 1) within 4 weeks prior to the transplant surgery (at end-stage kidney disease), 2) 1-3 weeks after the transplant surgery, and 3) at 3 months after the transplant (after restoration of kidney function). Subjects were enrolled between October, 2018, to November, 2021, and all study visits were completed by March, 2022. Data collected includes: Demographic (age, biological sex at birth, race/ethnicity, marital status); clinical data (body mass index, dialysis status, type of dialysis, high vs. low risk immune-suppression protocol, antibiotics during study period); laboratory data (serum creatinine; estimated glomerular filtration rate; serum blood urea nitrogen; immunosuppression trough levels), and outcome data (symptoms such as pain interference, pain intensity, fatigue, anxiety, depression, sleep disturbance, acute rejection, delayed graft failure, graft loss, post-transplant infections, and health-related quality of life). Incidence and severity of symptoms, including pain interference, pain intensity, fatigue, sleep dysfunction, and anxiety/depression-like symptoms, were measured using the Patient Reported Outcome Measurement Systems (PROMIS) 57 v2.1. Health related quality of life was assessed using the Kidney Disease Quality of Life Short Form (KDQOL-SF v1.3). The objective of this longitudinal study is to characterize changes in microbial features at baseline, before restoration of kidney function, and over time, after restoration of kidney function via kidney transplantation, and to identify relationships between microbiome features and transplant outcomes (rejection, infection, delayed graft function, graft failure), symptom burden, and health-related quality of life. Shotgun metagenomic sequencing of the oral and gut microbiomes will allow a higher-resolution examination of the gut microbiome compared to 16S rRNA gene amplicon sequencing, and will provide direct evidence of metabolic capabilities of the microbiota. This approach will allow us to explore the dynamic nature of symptom burden, and the effects of demographic and clinical variables on the oral and gut microbiomes before and after restoration of kidney function.

Study phs002199

Anthropological dataset 1 for The admixture histories of Cabo Verde

Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) File name "eGAdeposit_233CaboVerde_SampleInfo_FINAL_01062022.txt" Column 1 corresponds to individual alphanumeric codes as in the "eGAdeposit_233CaboVerde_GenotypeFile_FINAL_01062022.vcf" genotype file Column 2 corresponds to individual's biological sex as per genetic inference Column 3 corresponds to individual's self-reported age in years Column 4 corresponds to individual's self-reported cumulated number of years spent in academic or professional education

Dataset EGAD00001008976

Kids First: Congenital Heart Defects and Laterality Birth Defects

Laterality defects occur in approximately 1:10,000 newborns and are associated with a range of structural birth defects and abnormalities of organ positioning. Gut malrotation, biliary atresia, asplenia or polysplenia, complex cardiovascular malformations, and midline defects such as neural tube defects, vertebral anomalies and rib fusions are found in various combinations in patients with laterality defects. In addition, a subset of laterality defects caused by abnormalities of cilia position or function are associated with additional medical problems such as chronic sinusitis and bronchiectasis that require specific preventive care; however these patients frequently are undiagnosed until late in disease course. The goal of this project is to elucidate the genetic architecture of laterality disorders in order to inform medical management and risk stratification and to prevent complications. Laterality disorders are genetically heterogeneous and we and others have previously identified single nucleotide variants inherited in an X-linked or autosomal recessive manner as explanations for a minority of cases. In addition, we have demonstrated copy number variants (CNVs) as a mechanism of disease that requires additional investigation. We hypothesize that the majority of cases result from complex genetic inheritance. We propose to investigate this hypothesis using a multifaceted analysis approach in our extremely well phenotyped cohort of 538 probands with laterality disorders. Nested within this cohort are 105 trios who have not had previous sequencing, probands who have had exome sequencing and are excellent candidates for gene discovery via whole genome sequencing (WGS), and families with multiple affected family members for family-based analysis. All trios will be analyzed by transmission disequilibrium test (TDT) including rare variant TDT. De novo mutations will also be identified from trios for potential gene discovery. Using all probands, we will identify the prevalence of pathogenic CNVs. In addition, we will perform burden analyses to identify genes, gene interactions, and pathways important for susceptibility to laterality disorders. Finally, our rare families with multiple affected members will be studied using family based segregation analysis. This comprehensive genetic analysis in patients with laterality disorders is necessary to identify the appropriate clinical diagnostic testing for risk stratification, to elucidate underlying genetic architecture and facilitate novel gene discovery, and to provide essential knowledge about genes and pathways impacting the development of laterality disorders.

Study phs002589

Transcriptomic Profile of Whole Blood Cells from Elderly Subjects fed Probiotic Bacteria Lactobacillus rhamnosus GG ATCC 53103 (LGG) in a Phase I Open Label Study

Open label study to evaluate the safety of Lactobacillus rhamnosus GG ATCC 53103 (LGG) in elderly subjects. Fifteen healthy elderly volunteers, ages 65-80 were enrolled in a study in which they received LGG capsules containing 1 x 1010 CFU, twice daily for 28 days and were followed through day 56. The study subjects completed a daily diary, a telephone call on study days 3, 7 and 14 and study visits at the Massachusetts General Hospital Clinical Research Center at baseline, day 28 and day 56. During each visit, the subject diary, interim history, potential adverse effects and concomitant medications were reviewed and vital signs and a physical examination were performed. Routine blood tests were obtained to monitor for safety during visits and nasopharyngeal and stool samples were collected for microbiome analysis. Volunteers interested in participating in the effect of LGG probiotic on the Human whole Blood Transcriptome substudy also had blood drawn for DNA and RNA extraction, after signing the substudy consent form. The main objective of the study was to assess the safety and tolerability of 2 x 1010 CFU LGG administered orally to elderly subjects for 28 days. Secondary objectives were to evaluate the richness and microbial diversity in nasopharyngeal and stool specimens using pyrosequencing, and to compare cytokine production in response to bacterial stimulation by following the kinetics of mRNA expression of pro and anti-inflammatory genes and different signaling pathways, in relation to changes in stool Bifidobacterium and Lactobacillus spp. The study was reviewed and approved by the Partners Human Research Committee (IRB # 2010P001695) and was registered at ClinicalTrials.gov (NCT01274598). The main results regarding the clinical signs and safety of intervention is published in PLoS One. 2014 Dec 1;9(12):e113456. doi: 10.1371/journal.pone.0113456. eCollection 2014. PMID: 25438151. RNA sequencing for transcriptome analysis was only done in 11 of the 15 subjects as RNA integrity and quantity had to be optimal for the three times where blood was collected in order for a subject to be included in the study. The information regarding the microbiome data associated with this study is presented in a separate paper, which can be found at dbGaP study accession, phs000896, and PMID: 25873374.

Study phs000928

Kids First: Genetics of Pediatric Germ Cell Tumors

The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the genomic and phenotypic data from this study are accessible through dbGaP. The data is also available at the Kids First Portal, where other Kids First datasets can also be accessed in the cloud for data analysis, data visualization, collaboration and interoperability, open to all researchers and developers.Pediatric malignant germ cell tumors (GCTs) represent approximately 6% of childhood cancers, including 3% of tumors in children aged 0-14 years and 15% of tumors in adolescents. GCTs are heterogeneous and grouped together due to the presumed common cell of origin, the primordial germ cell (PGC). GCTs typically occur in the testes or ovaries; however, extragonadal GCTs can occur and are likely a result of abnormal germ cell migration during development. Evidence suggests that GCTs, including those diagnosed in adults, are initiated in utero. Thus, alterations in normal embryonic development are likely to be especially relevant to GCT etiology. Germline susceptibility has not been evaluated in an agnostic fashion in pediatric GCT, mainly due to a lack of an adequate number of samples; however, emerging evidence supports a genetic etiology.In the two Kids First GCT projects, we will evaluate genetic susceptibility to intracranial and extracranial GCT by sequencing probands and their unaffected parents. The goals of the project are to: 1) evaluate the contribution of rare genetic variants in GCT through the use of aggregate burden tests, focusing on genes and established regulatory regions; 2) identify de novo SNVs and CNVs in pediatric GCT using a case-parent triad design; and 3) identify molecular signatures in GCT tumor specimens, overall and by age group and tumor characteristics. Whole Genome Sequencing (WGS) data generated through the Gabriella Miller Kids First Pediatric Research Program will provide an opportunity to investigate the genetic origins of GCT in a diverse set of samples. Given the limited knowledge of GCT etiology and biology, the results of the proposed analyses are likely to have a big impact on the field.

Study phs002322

Identification of improved IL28B SNPs and haplotypes for prediction of drug response in treatment of hepatitis C using massively parallel sequencing in a cross-sectional European cohort

The hepatitis C virus infects nearly 3% of the World’s population, causing severe liver disease in many. Standard of care therapy is currently pegylated interferon alpha and ribavirin (PegIFN/R), which is effective in less than half of those infected with the most common viral genotype. Two IL28B SNPs, rs8099917 and rs12979860, predict response to (PegIFN/R) therapy in treatment of hepatitis C virus infection. These SNPs were identified in genome wide analyses using Illumina genotyping chips. In people of European ancestry, there are 6 common (>1%) haplotypes for IL28B, one tagged by rs8099917 minor allele, four tagged by rs12979860. We used massive parallel sequencing of the IL28B and IL28A gene regions generated by PCR from pooled DNA samples from 100 responders and 99 non-responders to therapy, to identify common variants. Variants that had high odds ratios and were validated were then genotyped in a cohort of 905 responders and non-responders. Their predictive power was assessed, alone and in combination with HLA-C. Only SNPs in the IL28B linkage disequilibrium block predicted drug response. Eighteen SNPs were identified with evidence for association with drug response, and with a high degree of confidence in the sequence call. We found that two SNPs, rs4803221 (homozygote minor allele positive predictive value (PPV) of 77%) and rs7248668 (PPV 78%), predicted failure to respond better than the current best, rs8099917 (PPV 73%) and rs12979860 (PPV 68%) in this cross-sectional cohort. The best SNPs tagged a single common haplotype, haplotype 2. Genotypes predicted lack of response better than alleles. However, combination of IL28B haplotype 2 carrier status with the HLA-C C2C2 genotype, which has previousl y been reported to improve prediction in combination with IL28B, provides the highest PPV (80%). The haplotypes present alternative putative transcription factor binding and methylation sites. Massive parallel sequencing allowed identification and comparison of the best common SNPs for identifying treatment failure in therapy for HCV SNPs tagging a single haplotype have the highest PPV, especially in combination with HLA-C. The functional basis for the association may be due to altered regulation of the gene. These approaches have utility in improving diagnostic testing and identifying causal haplotypes or SNPs.

Study EGAS00001000096

Programmatic submission based on XML

Programmatic submissions (XML based) For further information please check our Submission FAQs, submission quickguide as well as submission terms! Introduction Besides the Submitter Portal tool, EGA supports programmatic sequence and clinical data metadata submissions. If you are not sure what this means, you may want to explore our brief metadata introduction. Programmatic submissions are recommended for array-based submission. Moreove, it may be of help if your submission is recurrent or it is difficult to manage manually due to its sheer size. Otherwise, we highly recommend using the Submitter Portal to perform submissions. In this page we will guide you through the required steps to programmatically submit data to the EGA. Programmatic submissions require your metadata to be structured for an easy and straightforward validation and archival. It basically consists in formatting your metadata as Extensible markup language (XML) files and submitting them to the EGA using the WEBIN Before submitting metadata to the EGA, it is important to ensure that the information in your XML files is compliant with our standards. You can see further details on how these standards are maintained at EGA at our EGA Schemas documentation page. Using WEBIN, you can validate your XML files against EGA's schemas to ensure that your metadata is compliant before submission. WEBIN services WEBIN production service WEBIN test service We advise you to submit your metadata to the test service when submitting to the production service for the first time. The test service is identical to the production service except that all submissions will be discarded in the following 24 hours. This allows you to learn about the submission process without having to worry about data being submitted. Authentication Authentication is required each time a submission is made. The submission service uses HTTPS protocol for metadata encryption and identification to provide a secure submission environment. Data file upload Both Runs and Analyses reference files (e.g. FASTQ need to be uploaded to the EGA before these metadata objects are submitted. In other words, if you submit a Run that references a file that we cannot find associated with your account, the metadata submission will fail. See further details on how to upload your files in our File Upload documentation. Metadata model of the EGA Our metadata model is formed by multiple metadata objects. Check further details in our documentation at our EGA Schema documentation page. Working with EGA XMLs files Now that the basic concepts of the EGA metadata have been described, you can start preparing your programmatic submission through XML. Here you will find the guidance on how to prepare the XML files. Programmatic Submission Tutorial Video Take a look at the Programmatic Submission Tutorial Video, which explains the workflow of a programmatic submission and goes over an example metadata submission. Programmatic Submission Tutorial Video. When building your XML files, we recommend using text editors (e.g.Sublime Text or VisualStudio) that allow you to visualise the structure of the XML with ease. Furthermore, these editors constantly check the consistency of the XML structure. Alternatively, and if the submission consists of a big number of objects (specially analyses), you may find the tool star2xml handy. This tool allows for a direct conversion between metadata in a tabular format (e.g. a spreadsheet) into XMLs. Identifying objects: Aliases and center names Every EGA object must be uniquely identified within the submission account using their alias attribute. The aliases can be used in submissions to make references between EGA objects. Let us dig into EGA's use of aliases and center names: alias: every object should have a name that is unique within your submission account. Once submitted successfully, every alias will be assigned a unique and permanent accession (EGA ID). refname: when an object references another by its alias, the alias of the referenced object goes into the "refname" attribute of the referencing object. For example, if a sample has the alias "sample1", and an experiment uses this sample, then the experiment's "EXPERIMENT/SAMPLE/refname" attribute should be "sample1". center_name: The "center_name" attribute is required within the submission XML and, if not provided when the object is submitted, it will be automatically filled using your default EGA account center_name. This element is the "controlled vocabulary acronym or abbreviation that is provided to the account holder when the account is first generated". If the submitter is brokering a submission for another institute, the submitter should use their special broker account name in broker_name while the data centre acronym remains in center_name. Log-in details should have been provided when you requested a submission account. Please contact our Helpdesk team if you have any questions. run_center: Many submitting centers contract out the actual sample sequencing to another center. In these cases, the sequencing center should be acknowledged in the run_center attribute. Again, this is controlled vocabulary and the acronym should be sought from EGA helpdesk before submitting. Please contact our Helpdesk team if you have any questions. Prepare your XMLs The goal of this section is to provide sufficient information to be able to create the metadata XML documents required for programmatic submissions. Please note, the EGA utilises the XML schemas maintained at the European Nucleotide Archive (ENA). It is important due to the fact that by using a similar system, some pieces of documentation from the ENA's programmatic submission can also help you with your programmatic submission to the EGA. For example, you can submit programmatically without using a Submission XML by following the steps at Submission actions without submission XML. A submission does not have to contain all different types of XMLs. For example, it is possible to submit only a few samples; or a study that is later to be referenced. You can submit each object one by one, or submit all in a batch: you choose what method of submission works best for you. We do recommend, nevertheless, that you submit the objects to be referenced (e.g. samples or studies) first, and the objects that reference these (e.g. experiments or datasets) afterwards. You can see a graphical view of these objects and their relationships at our EGA Schemas page. Independently of the submission scenario, you will always require a Dataset XML. The entity of a dataset is what is used to control access to the given data, in the form of runs or analyses. In other words, when a requester is granted access, it is through the dataset and the objects (e.g. runs or analyses) that the dataset contains, granting access to them in one go. Given the nature of the EGA, a dataset XML will always be required for the data access. First, we will differentiate between submissions of "raw" and "processed" data: Runs and Analyses, respectively. Run data submissions Raw data derives from instruments "as is". For example, a plain sequence file (e.g. FASTQ or unaligned BAM files) would be considered raw data. A typical raw (unaligned) sequence read submission consists of 8 XMLs: Submission Study Sample Experiment Run DAC Policy Dataset When technical reads (e.g. barcodes, adaptors or linkers) are included in the submitted raw sequences, a spot descriptor must be submitted to describe the position of the technical reads so that they can be removed. The following data files can be submitted without providing spot descriptor information in the experiment/run XML: BAM files (single reads) SFF files (single reads without barcodes) FastQ files (single reads without any technical reads) Complete Genomics files Analysis data submissions Processed data is, in some way, refined raw data. This includes raw data that has been processed by some form of analysis method (e.g. alignment, noise reduction, etc.). For example, an aligned sequence (e.g. BAM file), that was created using raw FASTQ files, would be a processed file. This category includes most types of data: sequence alignment files (e.g. BAM or CRAM), clinical data (e.g. phenopackets), sequence variation files (e.g. VCF), sequence annotation, etc. A typical EGA analysis data submission consists of 7 EGA XML: Submission Study Sample Analysis DAC Policy Dataset We accept three different types of analysis data submissions: BAM files (for multiple read alignments) VCF files (for sequence variations) Phenotype files (in any format) In anycase, keep in mind that samples must be created in order to be referenced in the analyses. In other words, the provenance of the information within the BAM, VCF and phenotype files Example XMLs Below you can find a non-extensive list of example XMLs with descriptive fields (i.e. explaining what to provide in each field). Furthermore, you can also find real examples (i.e. the true value of the provided fields) in our GitHub repository. Submission XML The submission XML is used to validate, submit or update any number of other objects. The submission XML refers to other XMLs. New submissions use the ADD action to submit new objects. Object updates are done using the MODIFY action and objects can be validated using the VERIFY action. Descriptive submission XML example True values submission XML example Study XML The study XML is used to describe the study containing a title, a study type and abstract as it would appear in a publication. Descriptive study XML example True values study XML example Please use the following notation within the property "STUDY_LINKS" when including PubMed citations in the Study XML: <STUDY_LINKS> <STUDY_LINK> <XREF_LINK> <DB>PUBMED</DB> <ID>18987735</ID> </XREF_LINK> </STUDY_LINK> </STUDY_LINKS> Sample XML The sample XML is used to describe the samples used to obtain the data, whether they were sequenced, measured in any other way, or have an associated phenotype. The mandatory fields include information about the taxonomy of the sample, sex, subject ID and phenotype. For example, the mandatory attribute fields for each sample would look like these, within the array of "SAMPLE_ATTRIBUTES": <SAMPLE_ATTRIBUTES> <SAMPLE_ATTRIBUTE> <TAG>subject_id</TAG> <VALUE>free text!</VALUE> </SAMPLE_ATTRIBUTE> <SAMPLE_ATTRIBUTE> <TAG>sex</TAG> <VALUE>female/male/unknown</VALUE> </SAMPLE_ATTRIBUTE> <SAMPLE_ATTRIBUTE> <TAG>phenotype</TAG> <VALUE>Free text, EFO terms (e.g. EFO:0000574) are recommended</VALUE> </SAMPLE_ATTRIBUTE> </SAMPLE_ATTRIBUTES> Sample is one of the most important objects to be described biologically, it is highly recommended that “TAG-VALUE” pairs are generated as SAMPLE_ATTRIBUTES to describe the sample in as much detail as possible. For example, were we to give the population ancestry of the sample, we could add a new attribute to the array, in which, for example, we would indicate that the sample derives from an individual of "Mende in Sierra Leone" (MSL), with an african ancestry: <SAMPLE_ATTRIBUTE> <TAG>Population</TAG> <VALUE>MSL</VALUE> </SAMPLE_ATTRIBUTE> Given that VALUE and TAG are free text, the combinations are limitless in order to give you full flexibility on the information you want to provide. We recommend you use the Experimental Factor Ontology (EFO) to describe the phenotypes of your samples. You can provide more than one phenotype by adding more items to the array of SAMPLE_ATTRIBUTES. Phenotypes considered essential for understanding the data submission should be provided. Each phenotype described should be listed as a separate sample attribute <SAMPLE_ATTRIBUTE> </SAMPLE_ATTRIBUTE>. There is no limit to the number of phenotypes that can be submitted. If a suitable EFO accession cannot be found for your phenotype attribute, please consider using another controlled ontology database (e.g. HPO, MONDO, etc.) before using free text. Descriptive sample XML example True values sample XML example Experiment XML The experiment XML is used to describe the experimental setup, including instrument platform and model details, library preparation details, and any additional information required to correctly interpret the submitted data. Where any of these values differ between runs, a new experiment object must exist, since runs are grouped by experiments. Each experiment references a study and a sample by alias, or if previously-submitted, by accession. Pooled data must be demultiplexed by barcode for submission. Descriptive experiment ( Illumina paired read ) XML example True values experiment ( Illumina paired read ) XML example Run XML The run XML is used to associate data files with experiments and typically comprises a single data file (e.g. a FASTQ file). Please note that pooled samples should be de-multiplexed prior submission and submitted as different runs. Descriptive run XML example True values run XML example Analysis XML Given that an analysis can be used to submit any type of processed data to the EGA, we will list below an example of each of the three most common types of analysis XMLs submitted to the EGA: sequence alignments (e.g. BAM files); sequence variation (e.g. VCF files); and clinical metadata or phenotypes (e.g. phenopackets). Regardless of the type of processed data submitted in the analysis, the analysis must be associated with a Study and can reference multiple types of other objects, from samples to experiments, if they are available at the EGA. Just like with Runs, whenever a file is submitted to the EGA through an analysis object, the file MD5 checksums must be present, in order for the EGA to validate file integrity upon transfer. This also includes index files when applicable (e.g. .bai.md5 files). Ideally, any analysis that uses a reference sequence for some kind of alignment (e.g. BAM, CRAM or VCF files), would contain metadata about the alignment, such as INSDC reference assemblies and sequences, by either using accessions (e.g. CM000663.1) or common labels (e.g. GRCh37). Read alignment (BAM) Analysis XML The Analysis can be used to submit BAM alignments to EGA. Only one BAM file can be submitted in each analysis and the samples used within the BAM read groups must be associated with Samples. Descriptive bam alignments XML example True values bam alignments XML example Sequence variation (VCF) Analysis XML The Analysis can be used to submit VCF files to EGA. Only one VCF file can be submitted in each analysis and the samples used within the VCF files must be associated with Samples. Download analysis XML (VCF) Phenotype files The Analysis XML can be used to submit phenotype files to the EGA. Only one phenotype file can be submitted in each analysis and the samples used within the phenotype files must be associated with EGA Samples. Download analysis XML (Phenotype) DAC XML The DAC XML describes the Data Access Committee (DAC) affiliated to the data submission. The DAC may consist of a group or a single individual and is responsible for the data access decisions based on the application procedure described in the POLICY.XML. As with any other object, if it was already submitted to the EGA, there is no need to submit it again: you can reference an existing object within the EGA. Hence, A DAC XML does not need to be provided if your submission is affiliated to an existing EGA DAC.. Further information on DACs can be found here, and you can always contact our Helpdesk team if you have further inquiries. Descriptive dac XML example True values dac XML example Policy XML The Policy XML describes the Data Access Agreement (DAA) to be affiliated to the named Data Access Committee. Descriptive policy XML example True values study XML example Dataset XML The dataset XML describes the data files, defined by the Run.XML and Analysis.XML, that make up the dataset and links the collection of data files to a specified Policy. The dataset xml is commonly the last metadata object to be submitted, since it references multiple other entities. Please consider the number of datasets that your submission consists of. For example, a case-control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Descriptive dataset XML example True values dataset XML example Validating and submitting your EGA Validating EGA's XMLs through Webin After you have ensured that the XMLs are properly formatted and contain all the required information. You can proceed to validate and submit your data. Use the curl command to validate your XML file: Once you have prepared your XML file and asserted you have access to Webin, you can validate your XML file programmatically against EGA's schemas using the curl command. There are multiple ways in which you can validate your XMLs. This variety has to do with the fact that: (1) there are 2 instances of Webin (test and production); and (2) that validation is a default step during submission. In other words, any time that you submit your data through Webin, it will be validated automatically before being accepted. This allows for 4 possible routes of validation, all having the same validation result: validating or submitting to either the production service or the test service of Webin. For example, directly validating a "study" object XML in the testing service (wwwdev…) would look like the following: curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" In this command, you would need to replace <USERNAME> and <PASSWORD> with your EGA account username and password, respectively. You would also replace <INPUT_FILE> with the path to your XML file. A mock example would look like the following: curl -u ega-test-data@ebi.ac.uk:egarocks -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" The validation attempt can have different results depending on the given arguments: If your XML file is valid according to EGA's schemas, you will see a message indicating that your XML file is compliant. For example, see below for our mock example, where the "success" was "true" (i.e. no validation errors found). Nevertheless, notice how the "<STUDY accession=" is empty: it is because we were simply validating, so the study did not get an accession or ID. <?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="receipt.xsl"?> <RECEIPT receiptDate="2023-04-11T15:19:28.850+01:00" submissionFile="submission-EBI-TEST_1681222768850.xml" success="true"> <STUDY accession="" alias="Mock example" status="PRIVATE"/> <SUBMISSION accession="" alias="SUBMISSION-11-04-2023-15:19:28:840"/> <MESSAGES> <INFO>VALIDATE action has been specified.</INFO> <INFO>Submission has been rolled back.</INFO> <INFO>This submission is a TEST submission and will be discarded within 24 hours</INFO> </MESSAGES> <ACTIONS>VALIDATE</ACTIONS> <ACTIONS>PROTECT</ACTIONS> If there are any errors or warnings, the tool will display them, allowing you to correct them before submitting your data to EGA. For example, in the following response, it is said that the object we were trying to submit was already existing, and therefore the "success" was "false". <?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="receipt.xsl"?> <RECEIPT receiptDate="2023-04-11T15:12:35.609+01:00" submissionFile="submission-EBI-TEST_1681222355609.xml" success="false"> <STUDY alias="Example!_Human Microbiome Project SP56J" status="PRIVATE" holdUntilDate="2023-03-11Z"/> <SUBMISSION alias="SUBMISSION-11-04-2023-15:12:35:576"/> <MESSAGES> <ERROR>In study, alias: "Example!_Human Microbiome Project SP56J". The object being added already exists in the submission account with accession: "ERP127584".</ERROR> <INFO>VALIDATE action has been specified.</INFO> <INFO>Submission has been rolled back.</INFO> <INFO>This submission is a TEST submission and will be discarded within 24 hours</INFO> </MESSAGES> <ACTIONS>VALIDATE</ACTIONS> <ACTIONS>PROTECT</ACTIONS> If the curl command retrieves no response at all, please double check if your username and password are correctly provided. Also notice the "ACTION=..." argument passed to the Curl command. This specifies the action to take during the call to Webin, so we do not need a "Submission" XML just for a validation attempt. See more at submission actions without submission XML. Furthermore, validation of multiple files or objects (e.g. sample, experiment, study…) can be done in a single command by adding more arguments (i.e. '-F'). For example: curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" -F "SAMPLE=@sample.xml" -F "DATASET=@dataset.xml" As mentioned above, beside "validate" action in the test environment, you can also validate your metadata by three other methods: "Validate" in the production server. From our example above, you simply need to take the "dev" away from the URL. curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://www.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" "Add" in the development server. From our example above, you would simply need to replace the action: from "validate" to "add". Whatever is submitted to this service will be discarded in 24h, so whether something gets submitted or not would not matter in the long run. curl -u <USERNAME>:<PASSWORD> -F "ACTION=ADD" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" "Add" in the productionserver. A combination of the previous two methods, which would render this attempt into a submission. This path is just to be taken when you are sure your metadata is compliant and what you want to submit. curl -u <USERNAME>:<PASSWORD> -F "ACTION=ADD" "https://www.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" What happens after the submission of a dataset XML? Once you have completed the registration of your dataset/s please contact our Helpdesk Team to provide a release date for your study. Please note that all datasets affiliated to unreleased studies are automatically placed on hold until the authorised submitter or DAC contact contact the EGA Helpdesk for the study to be released. We strongly advise you not to delete your data until EGA Helpdesk confirms that your data has been successfully archived.

Documentation submission/metadata/submission/programmatic-submission-xml

The HLA-DQβ1 insertion is a strong achalasia risk factor and displays a geospatial north-south gradient among Europeans

Idiopathic achalasia is a severe motility disorder of the esophagus and is characterized by a failure of the lower esophageal sphincter to relax due to a loss of neurons in the myenteric plexus. Most recently, we identified an 8 amino acid insertion in the cytoplasmic tail of HLA-DQβ1 as strong achalasia risk factor in a sample set from Central Europe, Italy, and Spain. Here, we tested whether the HLA-DQβ1 insertion also confers achalasia risk in the Polish and Swedish population. We could replicate the initial findings and the insertion shows strong achalasia association in both samples (Poland P = 1.84×10-04, Sweden P = 7.44×10-05). Combining all five European data sets – Central Europe, Italy, Spain, Poland, and Sweden – the insertion is achalasia associated with Pcombined = 1.67×10-35. In addition, we observe that the frequency of the insertion shows a geospatial north-south gradient. The insertion is less common in northern (around 6-7% in patients and 2% in controls from Sweden and Poland) compared to southern Europeans (around 16% in patients and 8% in controls from Italy) and shows a stronger attributable risk (AR) in the southern European population. Our study provides evidence that the prevalence of achalasia may differ between populations.

Study EGAS00001001515

German early-onset prostate cancer cohort of the Pan-Prostate Cancer Genome (PPCG) project

Prostate cancer is the most frequent malignant tumor in males and the second most frequent cause of cancer-related death. Currently, in Germany, more than 60,000 prostate cancers are diagnosed every year. Although most of these patients are treated in a curative attempt, more than 10,000 German men die from prostate cancer annually. Owing to the demographic changes of our society, a further doubling of prostate cancer incidences during the next 20 years is expected. Prostate cancer is generally considered a tumor of elderly men. However, a fraction of prostate cancers are diagnosed at the age of 55 years or less. For several reasons, these “early onset prostate cancers” may represent a key entity for the understanding of prostate cancer biology. First, it is likely that early onset prostate cancers represent a distinct molecular subgroup of prostate cancer (PCa), potentially characterized by relatively small numbers of genetic changes, some of which may be particularly strong driver mutations for PCa development. Second, a fraction of prostate cancers in young individuals could represent classical prostate cancers that are detected at a very early stage and might therefore have accumulated molecular changes/mutations occurring that are most instrumental for prostate cancer early detection. Third, PCa with hereditary backgrounds are likely to accumulate in the age group below 55 years. A comparison with other sample sets (e.g. from other ICGC consortia), a systematic genomic analysis of young men with PCa could therefore lead to the detection of mechanisms for hereditary PCa. Fourth, a better understanding of these tumors is particularly relevant as finding optimal treatment regimens is most critical in young cancer patients. We are analyzing the entire genomic DNA sequences of at least 200 PCas (and matched non-tumorous DNA) of young men (≤ 55y), to at least 30 fold coverage, and integrate single-nucleotide variants and genomic structural variations with differential methylation, mRNA and miRNA expression data.Tissues were collected at the University Medical Center Hamburg-Eppendorf. Sequencing was performed at DKFZ and NCT (Heidelberg), EMBL (Heidelberg), and MPIMG (Berlin). Data management and bioinformatic data analyses is being conducted at DKFZ.

Study EGAS00001003373

Mesothelioma Whole Genomes

Genomic architecture of mesothelioma parent study is project 925. This project is set up in parallel to project 925 in order to Whole genome sequence ten of the 59 tumours in that project.

Dataset EGAD00001001265

Epigenetic memory of SARS-CoV-2 mRNA vaccination in monocyte-derived macrophages

Immune memory is key to effective antimicrobial responses, but the impact of mRNA vaccines on this process is not fully understood. Our research shows that SARS-CoV-2 mRNA vaccines alter the epigenetic profile of human macrophages, specifically enhancing histone acetylation, which is linked to immune training. Significant epigenetic changes, along with increased cytokine release, require two vaccine doses. However, these effects diminish over time but can be restored with a booster dose six months later, maintaining a strong pro-inflammatory response.

Dataset EGAD50000000495

120 individuals from the TEENAGE study (Ntalla et al., 2013) have been genotyped on the Illumina HumanCoreExome-12v1-1_A array. This is a population-based study of adolescents from the Attica region in Greece

120 individuals from the TEENAGE study (Ntalla et al., 2013) have been genotyped on the Illumina HumanCoreExome-12v1-1_A array. This is a population-based study of adolescents from the Attica region in Greece

Study EGAS00001001733

Response labels from NABUCCO cohort 1 (NCT03387761)

Data from NABUCCO cohort 1 (NCT03387761). This dataset includes the Response labels used for the analysis of the data. Details about the clinical definitions of Response can be found on the paper (https://doi.org/10.1038/s41591-020-1085-z)

Dataset EGAD00001006853

10x Genomics Single Cell Gene Expression for SA1053EX1XB01608

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

Dataset EGAD00001009123

10x Genomics Single Cell Gene Expression for SA1053BX1XB01603

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1053 passage 1

Dataset EGAD00001009131

10x Genomics Single Cell Gene Expression for SA1047BX1XB01022

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1047 passage 1

Dataset EGAD00001009146

10x Genomics Single Cell Gene Expression for SA1050DX1XB01437

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

Dataset EGAD00001009126

10x Genomics Single Cell Gene Expression for SA1181AX1XB02700

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1181 passage 1

Dataset EGAD00001009135

10x Genomics Single Cell Gene Expression for SA1162BX1XB03004

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1162 passage 1

Dataset EGAD00001009138

10x Genomics Single Cell Gene Expression for SA1050EX1XB01442

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1050 passage 1

Dataset EGAD00001009141

10x Genomics Single Cell Gene Expression for SA1049CX1XB01422

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1049 passage 1

Dataset EGAD00001009140

10x Genomics Single Cell Gene Expression for SA1052JX1XB01535

10x Genomics Single Cell Gene Expression for High grade serous ovarian carcinoma patient-derived xenograft SA1052 passage 1

Dataset EGAD00001009134

Human tumor single-cell mutiome

We profiled 1 patient neuroblastoma-FOXR2 tumor sample by single-cell multiome RNA + ATAC. The raw fastqs are provided.

Dataset EGAD00001010902

A_study_of_the_genetic_basis_of_evation_by_Acute_Myeloid_Leukaemia_of_Graft_vs_Leukaemia_effects_after_allogeneic_bone_marrow_transplantation

Acute myeloid leukaemia (AML) is an aggressive and molecularly diverse disease with a poor overall survival of 20-25%. With an annual incidence of 2.9 per 100,000, AML is currently the commonest myeloid malignancy in Europe, yet the two main therapeutic options for this disease, anthracyclines and purine analogues, have remained unchanged for over 20 years. Currently patients are stratified at diagnosis according to a series of clinicopathological parameters (e.g. age, white cell count and presence/absence of previous clonal haematological disease) and molecular markers (e.g. chromosomal translocations/deletions, aneuploidy and mutations in genes such as FLT3 and NPM1). Patients with adverse prognostic features, whose prognosis is particularly poor (e.g. <15% long-term survival) are offered treatment with allogeneic bone marrow transplantation (allo-BMT) if a sibling or unrelated donor is available. This can significantly improve survival (e.g. up to 40% long-term survival in some contexts), albeit at the expense of significant toxicity and transplant-related mortality (TRM). Allo-BMT is thought to work in part by allowing the delivery of large doses of chemotherapy followed by haemopoietic "rescue" with donor haemopoietic stem cells (haemopoietic failure would otherwise ensue). However, potentially the most potent effect of allo-BMT is the cytotoxic effect of donor lymphocytes against AML blasts, a phenomenon known as graft-vs-leukaemia (GVL) effect. Increasingly, transplants using reduced chemotherapy intensity (mini-allografts) are being used that partially circumvent the toxicity from chemotherapy and rely on GVL to effect cure. Nevertheless, AML relapse after allo-BMT still occurs at a significant rate of up to 80% depending on the type of transplant. There is accumulating evidence that genetic events in residual leukaemic cells enable them to evade immunodetection and therefore survive the GVL effect and expand to cause relapse. The most striking example of this is the loss of HLA antigens after transplants in which donor and recipient are not fully HLA-matched. In these cases, the leukaemia "deletes" the genomic region containing the disparate HLA antigen which was preferentially targeted as "foreign" by the GVL effect. However, the genetic basis of immune evasion in the majority of transplants, which are fully HLA matched, is not known. One possibility is that loss of genes coding for antigens outside the HLA locus but which are also targets of GVL may operate, alternatively genetic events that affect processes downstream of immunological cytotoxicity may be responsible.The identification of genetic events that mediate immune evasion would not only facilitate the understanding of this process but can help plan therapeutic interventions that improve the outcomes of allogeneic transplantation for AML and other disorders. We intend to study this by conducting exome sequencing on 6 cases of AMLs from patients that attend my clinic at Addenbrooke's hospital and have relapsed after allogeneic transplantation. Samples from AML diagnosis, remission/normal and AML relapse (total n=18) will be studied to identify somatic mutations in the primary AML and those acquired by the relapsed clone. The 18 samples will also be studied by array CGH to detect regions of genomic amplification or deletion.

Study EGAS00001000145

10916 results for "division 1 coins fc 26 Buyfc26coins.com is FC 26 coins official site..AwVj"

in 47.68 milliseconds.

Single_cell_measurements_to_characterise_B_cell_repopulation_in_SLE_after_rituximab_therapy__a_pilot_study

Jeju Genome Project DAC

Characterizing the Neurobehavioral Phenotype(s) in MPS III (Pilot Study)

Molecular Determinants of Tumor Behavior in Early Lung Adenocarcinoma

Similarity and diversity of the tumor microenvironment in multiple metastases: critical implications for overall and progression-free survival of high-grade serous ovarian cancer.

Using_genetics_to_identify_cell_types_and_mechanisms_underlying_susceptibility_to_primary_sclerosing_cholangitis

Identifying genetic consequences of Epstein-Barr Virus transformation by comparing an individual’s genomic DNA with that of its lymphoblastoid cell line.

Using_genetics_to_identify_cell_types_and_mechanisms_underlying_susceptibility_to_primary_sclerosing_cholangitis

GAW16 Framingham and Simulated Data

Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer

Next Generation Mendelian Genetics: Congenital Hyperinsulinism

Study of Tumor Recurrence Related to the Expression of the PAX3-FOXO1 Oncogenic Transcription Factor in Fusion-Positive Rhabdomyosarcoma

Analysis of Epigenomes and Genome Topology in Colorectal Cancer

Normal Pressure Hydrocephalus

This study explored and validated the clinical application of targeted NGS of circulating tumor DNA in identifying tumor-specific mutations and uncovering clinical actionable targets in a variety of solid tumors in large patient cohorts.

Mapping the breast cancer metastatic cascade onto circulating tumour DNA using genetic and epigenetic clonal tracking

WES of adult intellectual disabilities with co-morbid psychiatric disorders (2019-08-07)

NHGRI Genome Integrity of iPSCs Study

DNA methylation array study for 7 pairs of primary NSCLCs and distant metastases

Kidney_tumour_DNA

Single Cell Targeted Sequence Capture

EGAD00000000008

NHLBI TOPMed: The Genetics and Epidemiology of Asthma in Barbados

Transcriptomic Analysis of Pluripotent Stem Cell-Based Model of Human Amniogenesis

HuBMAP: A 3-D Tissue Map of the Human Lymphatic System

Genomic landscape of Ewing sarcoma (ICGC project)

Fixation effects on variant-calling in a clinical resequencing panel

Mitochondrial DNA mutations contribute to autism and also to the characteristics of mitochondrial disorders present in patients with autism spectrum disorders

NOTCH1 fusion genes in pediatric T-cell lymphoblastic lymphoma hallmark a common high-risk subgroup with blood TARC levels as possible biomarker

scRNAseq of ARID1B+/+ (control) and ARID1B+/- human telencephalic organoids at D120

Clonal diversity analysis and inter/intra-organ heterogeneity in urothelial carcinoma under immunotherapy

Interval whole-genome sequence (WGS) data

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC -- CA209-009

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC -- CA209-010

Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC-- CA209-025

Sequence-Based Analysis of Human Breast Tumors

Compound heterozygous variants in LAMC3 in association with posterior periventricular nodular heterotopia

Biological Determinants of Peritoneal Dialysis Outcomes

National Institute on Aging (NIA) Long Life Family Study (LLFS)

arcOGEN_HumanCoreExome-12v1-1_subset_2

CIRCLE-seq of PDO

Colorectal_organoids_and_tumoroids___pulldown

10x Genomics Single Cell Gene Expression for SA1051AX1XB01452

10x Genomics Single Cell Gene Expression for SA1052DX1XB01519

10x Genomics Single Cell Gene Expression for SA1050FX1XB01446

10x Genomics Single Cell Gene Expression for SA1093CX1XB01917

10x Genomics Single Cell Gene Expression for SA1049AX1XB01417

10x Genomics Single Cell Gene Expression for SA1091AX1XB01790

10x Genomics Single Cell Gene Expression for SA1052BX1XB01516

10x Genomics Single Cell Gene Expression for SA1096AX1XB02034

Breast Cancer Follow Up Series

Myocardial Infarction Genetics Exome Sequencing Consortium: German Heart Center in Munich

Mutational Landscape of MCPyV-Positive and MCPyV-Negative Merkel Cell Carcinomas

Study of Cutaneous Biology of Cutaneous T Cell Lymphoma

Whole-exome sequencing profiling of patients with metastatic prostate cancer at VHIO

MOSAIC - Multi-Omics Spatial Atlas In Cancer

Genomic landscape of poorly differentiated thyroid carcinoma

RNAseq of medulloblastoma data (MB_COMICS cohort)

OTOF mutation analysis with massively parallel DNA sequencing in 2,265 Japanese sensorineural hearing loss patients.

Analytical study of protein function and RNA expression involved in predicting treatment efficacy and adverse event development in lung cancer radiotherapy.

Development of blood-based biomarkers for precision medicine in castration-resistant prostate cancer

Deciphering the aggressive nature of morphoeic basal cell carcinoma

IMMUcan Lung NSCLC2 cohort

Flexible and rapid validation of structural variants using adaptive sampling

Policy Documentation

Sequencing of heritable Bleeding and Platelet Disorders

TRACERx 100: RNAseq data from the first 100 TRACERx tumours

Exome_sequencing_of_a_cohort_of_Rett_syndromelike_patients

Sequencing of liver cancer cell lines

Whole genome and RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

Molecular subtypes of malignant peritoneal mesothelioma

Whole genome sequencing of patients affected by acute intermittent porphyria

glioblastoma single cell RNAseq

RNA sequencing of NK cells in human lung

RNA sequencing in primary human macrophages overexpressing ETS2

The Gut Microbiome of liver transplant recipients – Cross-sectional + Longitudinal (renal and liver)

Changes in Oral and Gut Microbiota and Incidence and Severity of Patient-Reported Symptoms in Pre- and Post-Kidney Transplant Patients

Anthropological dataset 1 for The admixture histories of Cabo Verde