12450 results for ""non-traditional+communal+storytelling+approach"+novel+segment+noted+in+critical+commentary"

in 228.78 milliseconds.

• small RNA next generation sequencing in head and neck cancer

  small RNA next generation sequencing in head and neck cancer

  Dataset EGAD00001008402

• Processed DNA methylome sequencing data

  The dataset contains methylation values of all SNP-filtered CpG sites for all samples from the air pollution study (total n=60). Nasal lavage samples were collected from n=29 moderately exposed (residing in Stuttgart) and n=31 lowly exposed (residing in Simmerath) individuals. For methods and study details, please see PMID 37343754.

  Dataset EGAD00001011208

• ChIP-sequencing in human monocyte differentiation

  This dataset consists of ChIP-seq data from human monocytes, monocyte-derived dendritic cells as well as monocyte-derived cells that were subjected to siRNA treatment targeting CTCF or RAD21. ChIP-sequencing was done for H3K27, RAD21 and CTCF. In total, the data set includes 120 samples.

  Dataset EGAD00001007954

• Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WGS

  Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WGS

  Dataset EGAD00001010042

• In this study single cell RNA-Seq data was used to train a deconvolution algorithm. The algorithm was validated on paired bulk RNA-Seq profiles.

  In this study single cell RNA-Seq data was used to train a deconvolution algorithm. The algorithm was validated on paired bulk RNA-Seq profiles.

  Dataset EGAD00001009688

• DigiPico sequencing data for the study of active mutational processes in HGSOC

  The dataset contains Bam files from DigiPico runs as well as bulk sequencing data used in the "A highly accurate platform for clone-specific mutation discovery enables the study of active mutational processes" publication.

  Dataset EGAD00001005118

• Predictor_RIO_TNBC (2019-04-03)

  In this study, samples fom a window study of the PARP inhibitor rucaparib in patients with primary triple negative or BRCA1/2 related breast cancer (RIO trial) will be investigated. Samples will undergo whole genome sequence and analysis, including use of HR Predict. . This dataset contains all the data available for this study on 2019-04-03.

  Dataset EGAD00001004894

• Total RNAseq in the sporadic ALS and healthy control motor cortex

  The motor cortex is the earliest affected brain region in ALS. This dataset contains total RNA sequencing (stranded, 2x101bp) data derived from the motor cortex of 11 sporadic ALS patients and 8 healthy controls.

  Dataset EGAD00001006022

• Nuclear Optimized 10x data

  Optimized 10x library to increase the coverage of selected nuclear variants from 3’ 10x Genomics scRNAseq data. SNVs were selected based on exome data and criteria described in the Supplementary Information of the manuscript.See details of the experimental method in the methods section of the manuscript

  Dataset EGAD00001010192

• MutaSeq data for A.10-12

  MutaSeq was applied to CD34+ cells from patient samples A.10, A.11 and A.12 of the study. The protocol followed is described in https://doi.org/10.1038/s41467-021-21650-1 and in the methods of the manuscript

  Dataset EGAD00001010189

• Gene expression in human monocyte differentiation

  This dataset consists of RNA-seq data from human monocytes, monocyte-derived dendritic cells or monocyte-derived macrophages as well as monocyte-derived cells that were subjected to siRNA treatment targeting CTCF or RAD21. In total, it includes 63 samples.

  Dataset EGAD00001007956

• Whole exome sequencing of 27 Greenlanders

  The data contain whole exome sequencing of 27 Greenlanders in nine trios. Data were produced by Agilent SureSelect capture followed by paired-end Illumina HiSeq 2000 sequencing to a depth of 90.1X. More details on processing and analysis can be found in Moltke et al, Nature 2014 (PMID 25043022).

  Dataset EGAD00001003813

• EPITREAT pilot cohort

  Benchmark data set containing five tumor/normal pairs of non-small cell lung cancer (NSCLC) patients. Tissue pairs were screened with bisulfite (BS) sequencing, MeDIP methylation enrichment sequencing and RNA sequencing in order to identify differentially methylated and expressed spots in the genomes.

  Dataset EGAD00001003116

• Delineate genomic and epigenomic changes in esophageal squamous cell carcinoma following radiotherapy

  We performed whole-exome sequencing and whole epigenome sequencing (RRBS) of samples collected from different time points during radiotherapy from thirty-four ESCC patients. We compared the genetic and epigenetic features of the different time biopsy samples to reveal the changes in ESCC received radiotherapy.

  Dataset EGAD00001003799

• Edinburgh Naevi Cohort (2018-08-03)

  In this project we have sequenced the exome of skin moles (melanocytic naevi) and also normal skin from young and old people. We are interested in looking at the clonality of these lesions and the burden of UV mutations . This dataset contains all the data available for this study on 2018-08-03.

  Dataset EGAD00001004273

• GIS-LUNGTCR1-2016_WES-FASTQ

  This dataset contains FASTQ files for multi-region exome-sequencing of EGFR-mutant lung adenocarcinomas from Asian patient. There are 16 patients and 95 samples in total, including 16 controls and 79 tumors. Multiple runs for each sample, and 368 fastq in total. Please refer to the sample-ID from filename for merging.

  Dataset EGAD00001001978

• 200PG : WGS Raw Sequence (fastq)

  200PG : WGS Raw Sequence (fastq) : Raw WG sequence data (fastq) in this dataset are from the 124 CPCGene Tumour/Normal Pairs used in the 200PG Study. https://www.ncbi.nlm.nih.gov/pubmed/28068672

  Dataset EGAD00001001094

• 4C-seq in endometrial healthy and tumor tissues

  4C-seq performed on 10 slices (30um thick) of fresh frozen endometrial tissues. These tissue include 2 healthy tissues and 4 tumor tisseus (post-menopausal patients) in replicate. The library has been performed using DpnII (primary) and NlaIII (secondary) restriction enzymes. Raw single-end fastq.gz files are provided.

  Dataset EGAD00001010897

• Understanding the development of resident memory T cells (Trm) in the human small intestine using integrative multiomic approaches: Paediatric RNA (2026-01-15)

  This study involves atlasing the development of the postnatal gut nervous system in order to elucidate the pathogenic mechanisms of Hirschsprung disease. . This dataset contains all the data available for this study on 2026-01-15.

  Dataset EGAD00001015797

• Measurable residual disease in elderly acute myeloid leukemia: results from the PETHEMA-FLUGAZA phase III clinical trial

  In our study, we hypothetyzed that CD34progenitors from cases with undetectable Minimal residual Disease (MRD) by flow cytometry would contain cells with leukemic-initiating-potential that could be identified on genetic (rather than phenotypic) grounds by Whole Exome Sequencing.

  Dataset EGAD00001006585

• Understanding the development of resident memory T cells (Trm) in the human small intestine using integrative multiomic approaches: Paediatric Spatial (2025-07-31)

  This study involves atlasing the development of the postnatal gut nervous system in order to elucidate the pathogenic mechanisms of Hirschsprung disease. . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015665

• Single-Cell Data from "Spatiotemporal T-cell tracking for personalized T-cell receptor T-cell therapy designs in childhood cancer"

  This dataset contains the FASTQ files from the Single-Cell GEx+TCR 10X Genomics data from the study "Spatiotemporal T-cell tracking for personalized T-cell receptor T-cell therapy designs in childhood cancer" (EGAS00001008174)

  Dataset EGAD00001015632

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age<20 0.043 Age>40 0.032 Age<30, ≥20 0.251 Age>30, ≤40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) - Genome-Wide Association Study Meta-Analysis

  Discovery, Biology, and Risk of Inherited Variants in Breast Cancer (DRIVE) was one of five projects funded in 2010 as part of the NCI's Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative (http://epi.grants.cancer.gov/gameon/). GAME-ON's overall goal was to foster an intra-disciplinary and collaborative approach to the translation of promising research leads deriving from the initial wave of cancer GWAS. Specific goals included replication of previous GWAS findings and identification of new susceptibility loci through meta analyses of existing GWAS data and fine mapping of identified loci to better pinpoint causal variants; and identify germline variants that are associated with risk of multiple cancers. The other four funded GAME-ON projects were: the ColoRectal TransdisciplinaryStudy (CORECT), Elucidating Loci Involved in Prostate Cancer Susceptibility (ELLIPSE), Follow-up of Ovarian Cancer Genetic Association and Interaction Study (FOCI), and Transdisciplinary Research in Cancer of the Lung (TRICL). To identify additional cancer risk loci, improve the precision of fine-mapping, and facilitate cross-cancer analyses, DRIVE investigators performed a meta-analysis of eleven genome-wide association studies of breast cancer: The Australian Breast Cancer Family Study (ABCFS), the British Breast Cancer Study (BBCS), the Breast and Prostate Cancer Cohort Consortium (BPC3), the Breast Cancer Family Registries (BCFR), the Dutch Familial Bilateral Breast Cancer Study (DFBBCS), German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC), the Helsinki breast cancer family Study (HEBCS), the Mammary Carcinoma Risk factor Investigation (MARIE), the Singapore and Sweden Breast Cancer Study (SASBAC), the Triple Negative Breast Cancer Study (TNBC), and the UK2 GWAS. These studies comprised a total of 16,062 cases and 46,157 controls. Imputation to the 1,000 Genomes Project Phase 1 v3 ALL reference panel was performed by study, and summary statistics from each study were combined using fixed-effect meta analysis.

  Study phs001263

• NEI CIDR Methylation Profiling of Primary Open Angle Glaucoma in GLAUGEN Samples

  This is a case-control study of Primary Open Angle Glaucoma (POAG). POAG is a progressive optic neuropathy that eventually leads to blindness. More than 30 million people worldwide have Primary Open Angle Glaucoma (POAG), of which greater than 3 million are blind. Gene expression changes in the retina have been observed for POAG. Several recent studies, including the GLAUGEN (Glaucoma Gene Environment) initiative have used GWAS to identify correlative regions of the genome. Despite this, the genetic basis of Glaucoma is not well understood. Epigenetic variation may account for low heritability and environmental effects on human disease. Despite the significant advances being made in understanding the role of epigenetics in gene regulation in other fields, little is known about the relationship between DNA methylation patterns, retinal gene expression, and retinal disease. The goal of this study is to identify differentially methylated regions in the peripheral blood of patients with POAG. The case identification is as per the GLAUGEN description: Cases and controls were recruited from ophthalmology clinics and were examined by ophthalmologists. For cases the clinical exam included intraocular pressure measurements, optic nerve assessment and visual field evaluation. Controls had no family history of glaucoma, normal intraocular pressure and normal optic nerves. POAG and control samples come from Massachusetts Eye and Ear Infirmary (MEEI). These samples were collected and genotyped as part of the GLAUGEN study. From the MEEI, 50 patients were selected from POAG pedigrees, to include all the probands genotyped by CIDR and are currently undergoing exome sequencing, and to include additional genotyped probands who belong to pedigrees of sufficient size and structure that parent of origin effects could be evaluated. Additional individual-level phenotype and genotype data may be obtained through the authorized access portal of phs000308 (Geneva - Glaugen GWAS Study).

  Study phs000461

• ARDSnet and the iSPAAR Consortium: Genomic Basis of Susceptibility and Outcomes in Patients with the Acute Respiratory Distress Syndrome (ARDS)

  Acute Respiratory Distress Syndrome (ARDS)/ Acute Lung Injury (ALI) is a syndrome defined by the presence of acute hypoxemic respiratory failure, bilateral pulmonary infiltrates on chest radiograph, a known clinical risk factor (e.g. sepsis, pneumonia, trauma, gastric fluid aspiration, pancreatitis, massive transfusion), and the absence of physiologic or clinical evidence of congestive heart failure. The Identification of SNPs Predisposing to Altered ALI Risk (iSPAAR) study is a multi-institutional cooperative study, funded through the NHLBI Recovery Act, that assembled samples and phenotype information from existing cohorts. The consortium included samples from patients with ARDS from the NIH NHLBI ARDS Clinical Trials Network (ARDSNet). Samples were obtained from 3 interventional treatment trials in patients with ARDS, including the Fluid and Catheter Treatment Trial (FACTT), the Albuterol to Treat Acute Lung Injury (ALTA) trial, and the Omega-3 Fatty Acid/Antioxidant Supplementation for ALI trial (Omega). In addition to ARDSnet samples, samples from the other cohorts included cases of established ARDS but also controls: critically ill patients who were at-risk for ARDS but who did not develop ARDS during their hospital course. These cohorts included the Molecular Epidemiology of Acute Respiratory Distress (MEA) Study enrolled at the Harvard University/Massachusetts General Hospital, the Systemic Inflammatory Immune Response Syndrome (SIRS) Patient Database and ICU Traumatic Injury cohorts from Harborview Medical Center, and cohorts collected from the ALI research programs at the University of Pennsylvania and the University of California, San Francisco. The Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" box located on the right hand side of this top-level study page phs000631 ARDSnet iSPAAR Consortium. phs000334 ESP_LungGO_ALI phs000686 ALI_GeneticRisk

  Study phs000631

• After the completion of CINECA, EUCANCan, and euCanSHare. What's next?

  CINECA, EUCANCan, and euCanSHare were part of the EUCAN Cluster, made up of six projects that received funding under the same Horizon 2020 call. All EUCAN projects (CINECA, EUCANCan, EUCAN-Connect, euCanSHare, Receptor Plus, and ReCoDID) were aimed at facilitating data reuse and knowledge discovery by enhancing data exchange and long-term collaboration in the health field. Here are some highlights about EGA’s contribution to these projects. CINECA: advances in Federated discovery and infrastructure for cohorts CINECA (Common Infrastructure for National Cohorts in Europe, Canada, and Africa) developed a federated cloud-based infrastructure for making genomic and biomolecular data accessible. The project has assembled a virtual cohort of 1.4 million individuals from sources such as the EGA, CanDIG and H3Africa. The EGA–CRG co-leaded a work package Work Package 1 on Federated Data Discovery and Querying. Beacon v2, championed by Jordi Rambla and Lauren Fromont, has been one of the central elements for the discovery of human genetic and phenotypic data. The EGA-CRG contributed to the development of a model for cohort discovery inside the Beacon v2 model. The team also delivered a Discovery Portal was implemented to explore cohorts and individuals of synthetic data. It is a UI that gathers a network of Beacons, a service for query expansion, and a visualisation tool. Have a look at the Discovery Portal UI, gathering a network of Beacons. You will find entities such as the Barcelona Supercomputing Center (BSC), BioData.pt and the European Genomic Data Infrastructure (GDI), among others. euCanSHare: facilitation of data access management This joint EU-Canada project aimed to build a European and Canadian FAIR platform for cardiovascular data sharing and analysis. The EGA’s tasks contributed to the development of the data management plan and data flows, main web-portal and interoperability protocols. An important part of the EuCanShare platform is the data access manager, a tool for the data owners to control the access to their sensitive datasets. We built a user-friendly interface for data access committees (data owners) to easily manage their data requests and access credentials. The data access portal facilitates the creation and internal organization of the data access committees as well as the linkage of data usage conditions to specific datasets. The interface includes filters for browsing requests and page to visualize the request history helping with the handling of data access requests. EUCANCan: toward a federation of clinical institutions in oncology The EUropean-CAnadian CANcer Network worked towards building a federated network to advance personalized medicine in oncology, by promoting the standard analysis, management and sharing of harmonized genomic and phenotypic data. The EGA led tasks on defining data flows and preparing an adapted infrastructure for long-term data storage and sharing. One of the key contributions was the conception of the EGA communities, offering standard and interoperable solutions for data discovery, processing, and sharing to projects and institutions that would like to manage and share data in the context of the EGA ecosystem. What's Next? The participation in projects such as CINECA, EUCANCan, and euCanSHare provide us with experience for future projects. We are happy to enhance data sharing and reuse, vital for advancing clinical and genomic research. The Discovery Portal is a wonderful proof of concept for the Beacon network. Next, we will finalise both the network and the user interface, and make sure it can be applied to more clinically-centred settings like hospitals. Most data hosted at the EGA are about cancer research. Currently, we contribute to building tools and infrastructure to empower oncology research in several European projects such as EUCAIM, EUCANIMAGE and EOSC4Cancer. We also do not lose sight of initiatives in the field such as the International Cancer Genome Consortium (ICGC) with the project ARGO, whose data model was adopted in EUCanCan.

  Blog cineca-eucancan-and-eucanshare-were-concluded-in-june

• Population Structure and Genetic Diversity in Argentinean populations

  Argentina was one of the last places peopled when humans entered the Americas. Its earliest archeological sites are dated from 13,000 years BP, and throughout its history the region has exhibited broad cultural diversity, involving both hunter-gatherer and agro-pastoral societies, different linguistic families, the Southern expansion of the Inca Empire, the arrival of the Spanish conquistadors and slave trade from Africa. More recently, Argentina has had the highest proportion of influx of transoceanic migration between 1850 and 1940 of any Latin American country. Furthermore, the geographical distribution of immigrants was oriented towards the Pampa region of central-eastern Argentina and the Northeast, so different patterns of mixed ancestry throughout the country are expected. In this present work we aim to describe the history and structure of the Argentinean population. Thus far, we have collected DNA samples from 2904 participants from 15 dispersed regions in Argentina, from the Andean populations in the Northwest to the river lands of the Northeast. Our preliminary data includes genome-scale Illumina Exome Array 250K genotypes, plus next-generation sequencing data from uniformly spaced genomic regions targeted with a genotype-by- sequencing strategy (which covers 1.5% of the genome), for 375 participants from 9 of the 15 populations. We will identify proportions and patterns of European, African and Indigenous American ancestry in the Argentinean cohort via local ancestry inference. The first series of analyses will focus on genomic tracts of Indigenous American ancestry for fine-scale examination of sub-continental structure by comparing to a panel of 493 samples from 52 Indigenous American populations from throughout the Americas. Furthermore, this work will serve as a test of different low-cost strategies (exome genotype array vs. genotype-by-sequencing) for accurate inference of population structure in extant populations.

  Study EGAS00001001663

• Substantial somatic genomic variation and selection for BCOR mutations in human induced pluripotent stem cells

  Human Induced Pluripotent Stem Cells (hiPSC) are an established patient-specific model system where opportunities are emerging for cell-based therapies. We compared and contrasted hiPSCs derived from different tissues, skin and blood, in the same individual. We show extensive single-nucleotide mutagenesis in all hiPSC lines, although fibroblast-derived hiPSCs (F-hiPSCs) are particularly heavily mutagenized by ultraviolet (UV)-related damage. We utilized genome sequencing data on 454 F-hiPSCs and 44 blood-derived hiPSCs (B-hiPSCs) to gain further insights. Across 324 whole genome sequenced (WGS) F-hiPSCs derived by the Human Induced Pluripotent Stem Cell Initiative (HipSci), UV-related damage is present in ~72% of cell lines, sometimes causing substantial mutagenesis (range 0.25-15 per Mb). Furthermore, we find remarkable genomic heterogeneity between independent F-hiPSC clones derived from the same reprogramming process in the same donor, due to oligoclonal populations within fibroblasts. Combining WGS and exome-sequencing data of 452 HipSci F-hiPSCs, we identify 272 predicted pathogenic mutations in cancer-related genes, of which 21 genes were hit recurrently three or more times, involving 77 (17%) lines. Notably, 151 of 272 mutations were present in starting fibroblast populations suggesting that more than half of putative driver events in F-hiPSCs were acquired in vivo. In contrast, B-hiPSCs reprogrammed from erythroblasts show lower levels of genome-wide mutations (range 0.28-1.4 per Mb), no UV damage, but a strikingly high prevalence of acquired BCOR mutations in ~57% of lines, indicative of strong selection pressure. All hiPSCs had otherwise stable, diploid genomes on karyotypic pre-screening, highlighting how copy-number-based approaches do not have the required resolution to detect widespread nucleotide mutagenesis. This work strongly suggests that models for cell-based therapies require detailed nucleotide-resolution characterization prior to clinical application.

  Dataset EGAD00001007029

• Genome-wide differential DNA methylation signatures in pediatric acute lymphoblastic leukemia

  The aim of our study is to provide a comprehensive analysis of DNA methylation in a large collection of primary pediatric acute lymphoblastic leukemia (ALL) samples taken at diagnosis and relapse of the disease as well as non-leukemic control blood cells from healthy individuals. Complementary gene expression data available at the Gene Expression Omnibus under series GSE26878.

  Study EGAS00000000135

• Summary Statistics GWAS SSNS

  Column 1 rsid: SNP identifier;Column 2 chromosome: name of chromosome on which the SNP is located;Column 3: position: base pair position on the chromosome;Column 4 minor_test_allele: the base that constitutes the minor allele;Column 5 major_allele: the base that constitutes the major allele;Column 6 maf: the frequency of the minor allele, indicated as a fraction of 1;Column 7 allele_freq_cases: the minor allele frequency in cases;Column 8 allele_freq_controls: the minor allele frequency in controls;Column 9 regression_pvalue: the p-value for the difference in allele frequency between cases and controls;Column 10 odds_ratio: the odds ratio, as calculated using logistic regression under an additive model with adjustment for the first ten principal components of ancestry

  Dataset EGAD00010002316

• Relating Clinical Outcomes in Multiple Myeloma to Personal Assessment of Genetic Profile

  The Multiple Myeloma Research Foundation (MMRF) CoMMpass (Relating Clinical Outcomes in MM to Personal Assessment of Genetic Profile) trial (NCT01454297) is a longitudinal observation study of 1000 newly diagnosed myeloma patients receiving various standard approved treatments that aim at collecting tissue samples, genetic information, Quality of Life (QoL) and various disease and clinical outcomes over 10 years.

  Study phs000748

• Substance Dependence GWAS in European- and African - Americans

  This study includes SSADDA (Semi Structured Assessment for Drug Dependence and Alcoholism) assessed subjects (mostly unrelated, but including some affected sibling pairs) recruited in the course of several substance dependence genetics projects. The sample includes 1,531 self-reported African-American (AA) subjects, 1,339 self-reported European-American (EA) subjects, and 2 who reported race as "unknown" or "missing".

  Study phs000952

• Clonal Architectures and Driver Mutations in Metastatic Melanomas

  This study contains sequence data from 15 patients with stage IV melanoma, including the whole genome sequence of 15 metastatic tumors and corresponding normal blood samples from 13 cases, and targeted capture sequence of four synchronous metastatic samples from two additional cases. These data provide a comprehensive survey of the clonal architecture and associated driver mutations in metastatic melanoma.

  Study phs001241

• Gene Expression Analysis in Clonal Evolution of Fanconi Anemia

  We examined hematopoietic progenitor cells derived from iPSCs from patients with Fanconi anemia, including bone marrow failure cells (FANCA-/- HPCs), 'healthy', complemented cells (FANCA-/- cells with a wild-type FANCA cDNA), MDS-like cells (FANCA-/- HPCs with introduced mutations in RUNX1 and other MDS-associated genes), and Fanconi AML-like cells ('FAL'; MDS-like cells expressing FLT3-ITD).

  Study phs003024

• Raw scRNA-seq data from B-lineage cells in the blood of celiac disease patients

  Raw scRNA-seq data from 355 IgA+ peripheral blood B-lineage cells of two untreated celiac disease patients. The data was generated with the Smart-seq2 protocol and sequenced on a NextSeq500 instrument (Illumina) with 75 bp paired-end reads in high-output mode. The dataset contains R1 and R2 reads for each single cell (fastq.gz files) for cells passing quality control based on number of detected genes, reads, mitochondrial genes, reads mapping to the reference transcriptome and a productively rearranged immunoglobulin heavy chain IgA isotype reconstructed by the computational tool BraCeR. Metadata for the cells is provided in a csv file.

  Dataset EGAD50000000340

• Methylation sequencing dataset for "Molecular counting enables accurate and precise quantification of methylated ctDNA"

  Methylation sequencing dataset for "Molecular counting enables accurate and precise quantification of methylated ctDNA." This dataset was created by running samples through Northstar Response, where bisulfite converted samples are amplified in a multiplex PCR targeting more than 500 genomic regions. Samples in this dataset include contrived samples made from 84 different tumors DNA, each mixed with their matched buffy coat DNA at varying ratios, as well as cfDNA and buffy coat DNA samples collected from 67 cancer patients undergoing treatment. All samples were sequenced on Illumina NextSeq 2000 with single end 100 cycle sequencing; files are in fastq.gz format.

  Dataset EGAD50000001015

• Bulk RNAseq from in vitro generated macrophages and T cells

  Monocyte derived macrophages were polarised into M1 or M2 using IFNg+ ILP or IL-4 respectively (n =4) . Pan T cells were cultured with or without IL-2 for 4 days (n=4 - 6). Pan T cells were co-cultured with THP1 tumour cells for 20 hours in the presence or absence of ImmTAC molecules and in the presence or absence of M2 macrophages. Sorted T cells and macrophage populations prior and post co-culture were analysed by bulk RNA sequencing (60 million reads per sample) using the Illumina NovaSeq system

  Dataset EGAD50000001226

• Transcriptome of memory B cells with autoproliferation in MS

  Transcriptional profile of resting/hi and autoproliferating/Dim memory B cells in Multiple sclerosis patients. In brief, non-proliferating (CFSEhi) and AP+ (CFSEdim) CD19+ CD27+ B cells from PBMCs of 5 natalizumab-treated female RRMS (NAT) patients were sorted following 7 days of autoproliferation. Transcriptome libraries were constructed from the same samples, except for one sample pair, which was excluded due to limited input material (5 donors as for Methylome, D1; D2, D3, D5, D6; samples from donor D4 unfortunately technically failed). SMARTer Total Stranded RNA-seq library construction with ribosomal depletion was performed and then sequenced on NovaSeq S4 lane.

  Dataset EGAD50000001270

• Synchronous patterning of hiPSC-derived CNS progenitors generates comprehensive axial spinal cord organoids (CASCOs) containing diverse motor neuron population

  Dataset includes scRNA-sequencing data of cells isolated by dissociation of ~20 BJ WT day 20 hiPSC-derived MN embryoid bodies generated in ULA 96w plates following the protocol described in Rodriguez-Muela et al., JCI 2018). Droplet-based scRNA-seq was performed using 10X Genomics scRNA-sequencing was performed using 10X Genomics Chromium Single Cell Kit v3. The resulting sequencing reads were processed as described in Buchner et al 2024. Analysis of the count matrices was performed using the R toolkit for single cell genomics, Seurat v5.1.0, with R v3.3.3 “Angel Food Cake.”

  Dataset EGAD50000001301

• Mutational Profile in Newly Diagnosed Diffuse Large B-Cell Lymphoma: GAINED Study

  The GAINED study (NCT01659099) is a randomized phase 3 trial comparing obinutuzumab (G) to rituximab (R) in combination with ACVBP or CHOP14 induction, followed by PET-guided consolidation. This post-hoc analysis focuses on primary mediastinal B-cell lymphoma (PMBL) patients, confirmed through expert pathological review and characterized using gene-expression profiling (GEP) and Next-Generation Sequencing (NGS)

  Study EGAS50000000929

• Single cell RNAseq and TCRseq data from tumor and blood samples from 4 patients with muscle invasive bladder cancer

  For this dataset we performed single cell RNAseq paired with single cell TCR-seq on tumor and blood samples from 4 patients. This dataset contains 4 tumor samples as well as 4 blood samples. Each sample is made up of 2 sets of paired fastq files. The first pair contains reads corresponding to RNA transcripts (_Transcripts in file name), while the second pair contain reads corresponding to TCRs (_VDJ in file name). Sequenced on the Illumina NovaSeq6000 platform in a paired-end run using an SP flow cell (v1.5, 300 cycles).

  Dataset EGAD50000001381

• The Genomic Map of Poland in Open Access

  The main goal is to prepare and share WGS/WES of Polish population In this project NGS (next generation sequencing) was performed using Illumina NOVASEQ 6000 and Illumina DRAGEN aligner was used. Shared BAM and BAM.BAI files Library Construction Protocol: Illumina DNA PCR-Free Prep, Tagmentation. Reference Genome: GRCh37.

  Study EGAS50000000091

• Integrating Circulating Tumor DNA Analysis and Radiomics for Dynamic Risk Assessment in Localized Lung Cancer

  DNA was isolated from pre-treatment and mid-treatment plasma samples and matched germline samples from patients undergoing chemoradiation therapy for stage IIB-IIIB non-small cell lung cancer. Sequencing libraries were hybrid captured using custom selector pools designed to target genes frequently mutated in non-small cell lung cancer prior to ultra-deep next generation sequencing.

  Study phs003947

• Clonal hematopoiesis in rheumatoid arthritis

  To evaluate the clinical impact of CHIP on RA phenotypes and outcomes, we collected DNA samples from four distinct RA patient cohorts of newly diagnosed, previously untreated, RA patients without hematologic malignancies. A total of 573 RA patients and 163 healthy controls underwent targeted NGS sequencing using a sequencing panel consisting of 65 genes recurrently mutated in myeloid malignancies.

  Study EGAS50000000890

• RNA seq of intestinal biopsies and blood cells from patients with celiac disease and controls

  This study presents RNA sequenced from several intestinal phenotypes such as from patients with damaged intestinal mucosa as well as from those without a damaged intestine but still an autoantibody response to tissue transglutaminase (“potential celiac disease”) or those with treated celiac disease. By combining phenotypes in a much larger number of tissue samples from both peripheral blood and mucosal biopsies, we found highly differentially expressed genes, but also identify genes involved in controlling and triggering celiac disease associated changes. This study identifies molecular mechanisms involved in celiac disease and new possible targets for treatment and for identification of individuals at risk.

  Dataset EGAD50000001597

• Cancer genomics for elucidation of molecular mechanisms of carcinogenecis and progression in lung cancer

  The objective of this project is to analyze genomic aberrations and gene expression changes such as mutations, deletions, amplifications, and hypermethylation in human lung cancer cells at the somatic cell level, and to contrast these with clinicopathological information to elucidate the molecular mechanisms and characteristics of lung cancer development and progression at the genetic level.

  Study JGAS000756

• Whole-genome sequencing in gastric cancer (part2)

  we analysis structural variations (SVs) and mutational signatures via whole-genome sequencing of 168 GCs. Our data demonstrates diverse models of complex SVs operative in GC, which lead to high-level amplification of oncogenes. We find varying proportion of tandem-duplications (TDs) among individuals and identify 24 TD hotspots involving well-established cancer genes such as CCND1, ERBB2 and MYC.

  Study EGAS00001006575

• Adenoma to Carcinoma transition in Colorectal Cancer

  Although colorectal carcinoma development is well accepted as a step-wise and sequential process, it is commonly investigated using non-sequential adenoma and carcinoma samples. Here we compared molecular pathologies of the earliest carcinoma stages with those in their adenomatous precursors to unravel common and divergent genetic traits between matched neoplasms with a shared evolutionary history but different contemporary biology.

  Study EGAS00001003468

• Genomic landscape of signals of positive natural selection in North Eurasia

  We searched for the genomic signatures of positive selection in the genome-wide data of 432 people from eight different northern Russian populations (Russians from the Archangelsky and Vologdsky regions, Izhemski Komi, Priluzski Komi, Veps, Khanty, Mansi and Nenets) who were genotyped using microarrays for 700,000 SNPs (InfiniumOmniExpress-24v1-2_A1) through testing the extended haplotype homozigosity (EHH).

  Study EGAS00001003955