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• Targeted capture ctDNA Library CRCQV42Run42-10

  Targeted capture ctDNA Library CRCQV42Run42-10 from patient PBC0003643, saliva sample

  Dataset EGAD00001010823

• Targeted capture ctDNA Library CRCQV42Run42-12

  Targeted capture ctDNA Library CRCQV42Run42-12 from patient PBC0001375, plasma baseline sample

  Dataset EGAD00001010824

• Targeted capture ctDNA Library CRCQV42Run42-13

  Targeted capture ctDNA Library CRCQV42Run42-13 from patient PBC0001467, TNBC FFPE sample

  Dataset EGAD00001010825

• Targeted capture ctDNA Library CRCQV42Run42-14

  Targeted capture ctDNA Library CRCQV42Run42-14 from patient PBC0001375, TNBC FFPE sample

  Dataset EGAD00001010826

• Targeted capture ctDNA Library CRCQV42Run42-16

  Targeted capture ctDNA Library CRCQV42Run42-16 from patient PBC0001413, TNBC FFPE sample

  Dataset EGAD00001010827

• Targeted capture ctDNA Library CRCQV42Run42-17

  Targeted capture ctDNA Library CRCQV42Run42-17 from patient PBC0001375, saliva sample

  Dataset EGAD00001010828

• Targeted capture ctDNA Library CRCQV42Run42-4

  Targeted capture ctDNA Library CRCQV42Run42-4 from patient PBC0001375, plasma baseline sample

  Dataset EGAD00001010829

• Targeted capture ctDNA Library CRCQV42Run42-6

  Targeted capture ctDNA Library CRCQV42Run42-6 from patient PBC0001224, plasma 9 month sample

  Dataset EGAD00001010830

• Targeted capture ctDNA Library CRCQV42Run42-7

  Targeted capture ctDNA Library CRCQV42Run42-7 from patient PBC0001299, plasma 15 month sample

  Dataset EGAD00001010831

• Targeted capture ctDNA Library CRCQV42Run42-8

  Targeted capture ctDNA Library CRCQV42Run42-8 from patient PBC0003385, plasma 15 month sample

  Dataset EGAD00001010832

• Genome and transcriptome sequence data from a metastatic carcinoma of unknown primary patient

  Genome and transcriptome sequence data from a metastatic carcinoma of unknown primary patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011020

• Genome and transcriptome sequence data from a metastatic triple negative breast cancer patient

  Genome and transcriptome sequence data from a metastatic triple negative breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001011037

• SNF_OLINK_20

  Matrix of normalized values from Olink assay performed on baseline BM Plasma. The Olink Immuno-Oncology multiplex proteomic Panel included 92 proteins associated with human inflammatory conditions. Data is analyzed using real-time PCR analysis software via the Ct method and Normalized Protein Expression (NPX) manager. Data were normalized using internal controls in every single sample, inter-plate controls, negative controls and a correction factor and expressed as Log2 scale, which was proportional to the protein concentration. One NPX difference equals the doubling of the protein concentration.

  Dataset EGAD00001011147

• Geographic and age-related variations in mutational processes in colorectal cancer - filtered vcf files (Mutographs)

  Geographic and age-related variations in mutational processes in colorectal cancer - filtered vcf files (Mutographs)

  Dataset EGAD00001015486

• Geographic and age-related variations in mutational processes in colorectal cancer - copy number variants (Mutographs)

  Geographic and age-related variations in mutational processes in colorectal cancer - copy number variants (Mutographs)

  Dataset EGAD00001015487

• Geographic and age-related variations in mutational processes in colorectal cancer - patient metadata files (Mutographs)

  Geographic and age-related variations in mutational processes in colorectal cancer - patient metadata files (Mutographs)

  Dataset EGAD00001015437

• Geographic and age-related variations in mutational processes in colorectal cancer - sequence data (Mutographs)

  Geographic and age-related variations in mutational processes in colorectal cancer - sequence data (Mutographs)

  Dataset EGAD00001015485

• Genomic and transcriptomic landscape of T-cell lymphoblastic lymphoma compared to T-cell acute lymphoblastic leukemia: similar subtypes and different fusions

  Due to the lower incidence of T-LBL and difficulties in obtaining diagnostic T-LBL material, extensive research on T-LBL has been hampered whereas genetic aberrations in T-ALL are thoroughly characterized. Given the similarities and differences between T-LBL and T-ALL, the question has been raised whether T-LBL and T-ALL represent two different diseases or different manifestations of the same disease. This study aims to identify the genomic and transcriptomic landscape of T-LBL and compare the findings to what is found T-ALL. Comparison of the molecular aberrations between T-LBL and T-ALL can provide insights into the overlap and differences in malignant development between the two entities, which could lead to improved risk stratification in T-LBL in order to eventually adapt T-LBL treatment protocols based on molecular-genetic prognostic factors.

  Dataset EGAD00001015357

• Organoid Derivation Project - RNAseq (2024-10-14)

  Sequencing of tissue samples and their derived organoids. This dataset contains a subset of colorectal and colorectal liver metastasis samples.

  Dataset EGAD00001015425

• The Collaborative Study on the Genetics of Alcoholism (COGA)

  COGA is a family study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This project has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results, are included for a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3. As part of COGA, a set of informative families was selected to have Genome-Wide Association data obtained within families. Genotyping was performed using the Illumina Human OmniExpress array 12.VI to genotype 2,282 subjects selected from 118 densely affected families. Genotyping was performed at the Genome Technology Access Center at Washington University School of Medicine in St. Louis. In addition, we also included genotypes for subjects (n=275 subjects) from these 118 families who were genotyped in a previous case-control GWAS using the Illumina 1M array. For quality control purposes, 51 of the 275 subjects were genotyped again on the Illumina Human OmniExpress array at the Washington University School of Medicine core facility.In addition, exome sequencing data on a subset of individuals with GWAS were added in version 2 (v2). For v2, a subset had 30X Whole Genome Sequencing (WGS) as part of the NIDA Sequencing Initiative. The subset contained two distinct sets: Sibling pairs where one sibling had at least two dependence diagnoses in the set (alcohol, cannabis, cocaine, and opioid), and the other had none, and non-related Case-Control pairs matched for age and ethnicity where the cases had alcohol and at least 2 other dependence diagnoses and controls had none. After sequencing, some sibling pairs are re-classified as half siblings. Three VCF files (small variants, structural variants, and copy number variations) are provided. Additional substance use variables are made available in v2. We note that the full sample data are deposited in four dbGaP submissions and the sequenced samples are split across all four: CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study [phs000125]. GWAS data on cases (primarily probands) and controls drawn from the families. Families with highest density of alcohol dependence and/or extreme event-related oscillation data [phs000763]. GWAS data on 119 extended families of European descent are available here, along with extensive documentation. Study on the Genetics of Alcoholism (COGA): African American Family GWAS [phs000976]. GWAS data on all available COGA families of African descent are available. COGA: Smokescreen GWAS [phs001208]. GWAS data on all remaining COGA DNA samples, primarily of other racial background, were genotyped on the Smoke Screen array. A listing of all sequenced pairs is provided in the documentation to facilitate the merging of these samples.

  Study phs000763

• Evaluation of Nuclear DNA from Rootless Hairs for Forensic Purposes

  The study aims to overcome current limitations in the recovery of DNA from small, difficult forensic samples. Particularly, our goal is to produce a robust laboratory protocol and the accompanying software to accelerate adoption, as well as to evaluate the reliability and robustness of both the laboratory and computational aspects of generating genotype files from minute and/or degraded DNA samples, such as single, rootless hairs.The data accompanying this study includes raw, paired-end reads from high-throughput sequencing of two panels of saliva, head hair, and pubic hair samples collected from anonymous volunteers at the University of California, Santa Cruz. The smaller set (Hair1.0) comprises 8 individuals, while the larger (Hair2.0) comprises 50 individuals, with 3 overlapping individuals between the two panels identified in post-collection analysis. We did not collect phenotype data or personally identifying information from the participants. For the Hair2.0 panel, only a subset of volunteers provided pubic hairs for DNA extraction and sequencing. Also included are saliva-derived genotype array data for all 8 individuals in the Hair1.0 panel and 44 of 50 individuals in the Hair2.0 panel.

  Study phs002979

• A Microwell Platform for High-Throughput Longitudinal Phenotyping and Selective Retrieval of Organoids

  In traditional bulk culture, organoids tend to overlap, hindering the analysis of individual organoid characteristics in a high-throughput manner. Additionally, variations in the local spatial properties of the bulk matrix make it challenging to distinguish whether phenotypic differences between organoids stem from inherent cellular disparities or disparities in the microenvironment. To address these challenges, we have developed a microwell-based technique that facilitates the quantification of image-based parameters for organoids grown from single cells. Furthermore, these organoids can be easily retrieved from their respective microwells for molecular profiling. By employing a deep-learning image processing pipeline, we conducted a comprehensive assessment of various phenotypic traits in two CRISPR-engineered human gastric organoid models. This analysis encompassed growth rates, cellular movement, and apical-basal polarity. Through our investigation, we successfully identified genomic alterations associated with increased growth rate, as well as changes in accessibility and expression patterns correlated with apical-basal polarity. This novel methodology offers a valuable tool for studying organoid behavior at a single-cell level, enabling researchers to gain deeper insights into organoid biology and associated genetic modifications.

  Study phs003315

• Genetic Underpinnings of Ethnic Disparities in Bone Toxicities Between Hispanic and Non-Hispanic Children Treated for Acute Lymphoblastic Leukemia

  Acute lymphoblastic leukemia (ALL) is the most common malignancy among children and young adolescents. More than 90% of children are cured with a combination of multiple chemotherapeutic drugs. Some may suffer from debilitating toxicities due to the cytotoxic drugs, necessitating pharmacogenetic research to search for genetic markers predictive of treatment toxicities, so that treatment can be better tailored based on patients' genetic makeup. Bone toxicities, including osteonecrosis and fractures, most often due to glucocorticoids, are the most common complications in ALL, which have long-lasting detrimental impact on the still developing skeletons in children. In DFCI ALL Consortium Protocol 05-001, a multi-center clinical trial for childhood ALL conducted in Canada and the US, we found that Hispanic children had less drug toxicities to their bones than non-Hispanic children. Although reasons for the observed ethnic differences are largely unknown, patients' inherited genetic background may be at play. This study seeks to perform a novel pharmacogenomic study based on multi-site clinical trials DFCI ALL Consortium Protocol 05-001 and 11-001 to identify genetic underpinnings of ethnic disparities in bone toxicities.

  Study phs002317

• CONNECTS Master Protocol for Clinical Trials targeting Macro- and Micro-Immuno-Thrombosis, Vascular Hyperinflammation, and Hypercoagulability and Renin-Angiotensin-Aldosterone System (RAAS) in Hospitalized Patients with COVID-19 (ACTIV-4 Host Tissue)

  ACTIV 4 Host Tissue is a shared-placebo clinical trial platform evaluating therapies targeting the host response to COVID-19 in hospitalized patients. The overarching goal of the platform was to find effective strategies for inpatient management of patients with COVID-19. Therapeutic goals for patients hospitalized for COVID-19 include hastening recovery and preventing progression to critical illness, multiorgan failure, or death. Our objective is to determine whether modulating the host tissue response improves clinical outcomes among patients with COVID-19. Three trials were implemented to investigate three agents: TXA-127, TRV-027, and Fostamatinib. These agents all impact the host tissue response in COVID-19 via a number of unique mechanisms, including potential beneficial effects on the RAAS system and formation of neutrophil extracellular traps (NETs). Each trial evaluated the efficacy of these agents' ability to impact the host tissue response and improve outcomes in patients hospitalized with COVID-19. We found no evidence that any of the three agents significantly improved clinical outcomes as measured by the primary outcome, oxygen free days through day 28.

  Study phs003708

• DynaTag for efficient profiling of transcription factors in small samples and single cells

  Systematic discovery of transcription factor (TF) landscapes in low-input samples and at single cell level is a major challenge in the fields of molecular biology, genetics, and epigenetics. To address this, we present here cleavage under Dynamic targets and Tagmentation (DynaTag), which allows robust mapping of specific TF-DNA interactions via the use of a physiological salt solution during sample preparation. Using this method, we revealed occupancy alterations for 15 different TFs in stem cell and cancer tissue models. Of note, we showcased for NANOG, MYC, and OCT4 differentially occupied genomic loci during stem cell differentiation, both in bulk and at single-cell resolution. DynaTag demonstrated superior signal-to-background ratio and occupancy resolution in comparison to CUT&RUN and ChIP-seq. In addition, a model for small cell lung cancer chemotherapy treatment in vivo showed increased chromatin occupancies of the gain-of-function mutant P53 p.R248Q, FOXA1, and MYC at altered gene pathways, such as epithelial-mesenchymal-transition. Altogether, these results highlight the technical advancement of DynaTag to uncover TF landscapes in cell models and in tissues of a complex disease model.

  Study EGAS50000001074

• The identification of genetic vulnerabilities in head and neck cancers for the development of novel treatments.

  The global cancer burden is expected to double by the year 2030 and this will disproportionately affect the Asian continent. Head and neck squamous cell carcinoma (HNSCC) is endemic in Asia. It is the sixth most common cancer worldwide and the second most common in Malaysia, with approximately 600,000 new cases per year globally. Longterm survival remains less than 50%, underscoring the need for better therapeutic strategies. In this proposal we aim to bring new technological advancements in the identification of critical genes in HNSCC and the identification of compounds for the development of new therapies in HNSCC. We propose to genomically characterise 16 unique Asian H&N cancer cell lines, to classify sub groups where identification of essential genes that can be targeted for tumor control can be applied in a more rational way. Further, we propose to use zebrafish, an established drug discovery platform to identify promising pathway-specific compounds that could be further studied using CRISPR/Cas9 lethality screens and biological models to better identify novel therapeutic strategies to combat this major health problem in Asia.

  Study EGAS00001002682

• Detection of rare mutations, copy number variation, and DNA methylation in the same template DNA molecules

  The analysis of cell-free DNA (cfDNA) from plasma offers great promise for the earlier detection of cancer. At present, changes in DNA sequence, methylation, or copy number are the most sensitive ways to detect the presence of cancer. To further increase the sensitivity of such assays with limited amounts of sample, it would be useful to be able to evaluate the same template molecules for all these changes. Here we report an approach, called MethylSaferSeqS, that achieves this goal, and can be applied to any standard library preparation method suitable for massively parallel sequencing. The innovative step was to copy both strands of each DNA-barcoded molecule with a primer that allows the subsequent separation of the original strands (retaining their 5-methylcytosine residues) from the copied strands (in which the 5-methylcytosine residues are replaced with unmodified cytosine residues). The epigenetic and genetic alterations present in the DNA molecules can then be obtained from the original and copied strands, respectively. We applied this approach to plasma from 265 individuals, including 198 with cancers of the pancreas, ovary, lung and colon, and found the expected patterns of mutations, copy number alterations, and methylation. Furthermore, we could determine which original template DNA molecules were methylated and/or mutated. MethylSaferSeqS should be useful for addressing a variety of questions relating genetics and epigenetics in the future.

  Study EGAS00001006839

• Genetics of Chemotherapy Induced Peripheral Neuropathy in N08C1 and N08CB

  Chemotherapy-induced peripheral neuropathy (CIPN) is a common and potentially dose-limiting toxicity of chemotherapy treatment. CIPN severity varies widely between cancer patients, and previous studies had found evidence of genes and single nucleotide variants (SNV) being associated with CIPN. The goal of this study was to further identify genetic markers and pathways associated with CIPN severity using whole exome sequencing (WES) and whole genome sequencing (WGS) of participants in two clinical studies which collected longitudinal patient-reported outcome (PRO) measures of CIPN. NCCTG/Alliance study N08C1 was a prospective cohort study of the natural history of paclitaxel-associated acute pain syndrome (P-APS) and CIPN. NCCTG/Alliance trial N08CB was a randomized, placebo-controlled trial of calcium and magnesium for prevention of oxaliplatin-induced sensory neuropathy in which the treatment had no significant effect on either acute pain or sensory neuropathy. Both N08C1 and N08CB collected patient assessments of CIPN symptoms before each cycle of chemotherapy using the EORTC QLQ-CIPN20 instrument. For this study, CIPN cases were selected from each of N08C1 and N08CB as those patients with the most severe CIPN symptoms (assessed longitudinally). CIPN controls were selected as those with the least severe symptoms. WGS was obtained for N08C1 samples (WES had been obtained and analyzed previously), and WES was obtained for N08CB samples.

  Study phs001480

• High Density SNP Association Analysis of Lung Cancer

  This research builds upon an extensive resource of a case-control study that has been ongoing at the UT MD Anderson Cancer Center since 1991. To identify risk variants for lung cancer, we conducted a genome-wide association study. Cases are newly diagnosed, histologically-confirmed patients presenting at MD Anderson Cancer and who had not previously received treatment other than surgery. Controls are healthy individuals seen for routine care at Kelsey-Seybold Clinics, the largest physician group-practice plan in the Houston Metropolitan area. This lung GWAS led to the identification of a susceptibility locus for lung cancer at 15q25.1. We used data from 315,450 tagging SNPs in 1,154 current and former (ever) smoking cases of European ancestry and 1,137 frequency-matched, ever-smoking controls from Houston, Texas in the discovery followed by the replication of the ten SNPs most significantly associated with lung cancer in an additional 711 cases and 632 controls from Texas and 2,013 cases and 3,062 controls from the UK. Two SNPs, rs1051730 and rs8034191, were significantly associated with risk of lung cancer with combined analysis yielded odds ratios of 1.32 (P < 1X10-17) for both SNPs. These two SNPs mapped to a region of strong linkage disequilibrium within 15q25.1 containing PSMA4 and the nicotinic acetylcholine receptor subunit genes CHRNA3 and CHRNA5. (Nat Genet. 2008 May;40(5):616-22. PMID:18385676)

  Study phs000753

• Ischemic Stroke Genetics Study (ISGS)

  The third leading cause of death in the United States, stroke is an acute neurological event leading to death of neural tissues. Although the majority of strokes are ischemic strokes, meaning there is oxygen deprivation to the brain, almost 20% of strokes are hemorrhagic, resulting from bleeding into the brain. Stroke is a complex disorder and likely multigenic in nature, resulting from a combination of genetic and environmental factors. These well characterized risk factors that contribute to the incidence of stroke include hypertension, cardiac disease, sickle cell disease, hyperhomocysteinemia, family history of stroke and smoking. ISGS aim is to perform a prospective genetic association study of ischemic stroke focusing on the hemostatic system. ISGS is a 5-center case-control study of first-ever ischemic stroke cases and concurrent controls individually matched for age, sex and recruitment site. This data includes that from subjects both banked in the NINDS repository with biologicals publicly available, and those whose samples are not banked/not available. Important links to apply for individual-level data Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Participant Protection Policy FAQ --> This study utilized the NINDS Repository Cerebrovascular/Stroke Study, and neurologically normal controls from the sample population which are banked in the National Institute of Neurological Disorders and Stroke (NINDS Repository) collection for a first stage whole genome analysis.

  Study phs000102

• Natural History, Pathogenesis and Outcome of Melorheostosis

  Melorheostosis is a rare osteosclerotic disease resulting in exuberant excessive bone growth with a characteristic radiographic appearance often described as "dripping candle wax". As a result of these bony formations, patients report mild to moderate pain that interferes with their routine activities. It is usually diagnosed on radiographs but bone biopsy may be performed to exclude other osteosclerotic diseases and/or osteosarcoma. Deformities, limb-length discrepancy, muscle atrophy, neurological deficit have been reported as complications. A subset of patients have somatic mutations in MAP2K1. The cause of this disease is not known in all patients, the natural history poorly described and there is no clearly-defined systemic therapy. We propose a prospective observational study to investigate the natural history and pathogenesis of the disease. Subjects will undergo standardized initial evaluation and medically indicated testing. Skin biopsies may be performed to test for known mutations related to melorheostosis, and if negative affected bone and/or skin may be sent for genetic testing for acquired somatic mutations in genes that control bone homeostasis. Enrolled subjects will be followed every two to three years for assessment of disease progression and receive clinically indicated testing and treatment. The study of this rare bone disease offers the potential to generate new insights, provide answers as well as generate new questions into the biology of the skeletal and mineral metabolism.

  Study phs001976

• The Gene Partnership (TGP) - eMERGE Data

  The Gene Partnership (TGP) is a prospective longitudinal registry at Boston Children's Hospital (BCH) to study the genetic and environmental contributions to childhood health and disease, collect genetic information on a large number of children who have been phenotyped, and implement the Informed Cohort and the Informed Cohort Oversight Board (ICOB). The term "The Gene Partnership" reflects a partnership between researchers and participants. Children seen at BCH are offered enrollment, as are their parents and siblings. DNA is collected on all enrollees. BCH has a comprehensive EMR system, and virtually all inpatient and outpatient data are captured electronically. Clinical data in the BCH EMR is loaded in the i2b2 data warehouse which is available to investigators. Cases, phenotypes, and covariates are ascertained using the i2b2 database. Participants at BCH in TGP have consented to receive any research result and/or incidental finding that arises from studies using TGP that is approved by the Informed Cohort Oversight Board (ICOB) and is in accordance with the participants' preferences; results are returned through the Personally Controlled Health Record (PCHR). BCH and Cincinnati Children's Hospital Medical Center (CCHMC) have partnered as the Pediatric Alliance for Genomic and Electronic Medical Record (EMR) Research (PAGER) site for the eMERGE Phase II network for pediatric institutions, and the cohort for eMERGE at BCH is TGP.

  Study phs000495

• PGRN-RIKEN: Genetic Determinants of Clinical Cardiovascular Events in Patients Receiving Statins

  Coronary heart disease (CHD) is an important public health problem in developed countries. Statins are effective in the prevention and treatment of CHD; nevertheless, many patients receiving statins still suffer cardiovascular events (CV) such as heart attack. Identifying genetic variants responsible for differential clinical responses to statins will not only allow individual patients at high residual risk to be targeted for additional therapies, but also will define new biologic pathways contributing to statin response, and thus new targets for future therapies. Accordingly, the goal of this study is to identify genetic variants associated with clinical CV in patients receiving statins. Subjects identified for study are of European descent and include 1718 subjects with CV while on statins (cases) and 4172 subjects without CV while on statins (controls). Key research resources utilized in this effort include VanderbiltD's BioVU DNA databank and associated Synthetic Derivative database of clinical information, and software tools developed to identify drugs and clinical events using Electronic Health Record-derived structured and unstructured ("free text") data. Most cases and controls identified include three data types: ICD-9 codes, medication regimens, and medical test results. Genotyping, using IlluminaD's Infinium HumanOmniExpressExome BeadChip (OmniExpressExome), was performed by the RIKEN Integrative Medical Sciences Center (IMS) and supported by the Pharmacogenomics Research Network (PGRN)-RIKEN IMS Global Alliance.

  Study phs000963

• Large Scale Genotyping of Psychiatric Disorders

  Psychiatric disorders cause enormous human suffering and cost to society. The goal of this project is to elucidate the genetics of psychiatric disorders through a large consortium effort and genome-wide genotyping. The Psychiatric Genomics Consortium (PGC) (https://www.med.unc.edu/pgc) is an international consortium to pursue genome-wide analyses of common psychiatric disease. The PGC was founded in 2007 to unite investigators from around the world to conduct mega-analyses of individual genome-wide genotype data for schizophrenia (SCZ), bipolar disorder (BIP), autism (AUT), attention-deficit hyperactivity disorder (ADHD), and major depressive disorder (MDD). Subsequently, the PGC has expanded to include Tourette syndrome (TS), obsessive-compulsive disorder (OCD), eating disorders (ED), post-traumatic stress disorder (PTSD), and substance abuse (SUD). The PGC partnered with Illumina to develop the PsychChip, a custom GWAS array aimed at capturing common variation genome-wide for imputation, rare coding variation drawn from the exome chip and dense genotypes for loci with suggestive evidence for association across the initial PGC analyses of SCZ, MDD, BPD, ASD and ADHD. Samples (cases, controls, and families) were collected from Institutional Review Board-approved protocols that aim to study the genetics of psychiatric disorders. Genome-wide genotyping was performed at the Broad Institute (Cambridge, MA, USA) and the Mount Sinai School of Medicine Friedman Brain Institute (New York, NY, USA) using the PsychChip or Exome Chip.

  Study phs001413

• Identification of Cancer Predisposition Genes in Breast Cancer Families

  Breast cancer has a significant genetic component. The strongest epidemiologic risk factor is family history of the disease. Familial studies have identified a number of genes contributing to increased risk. Of these, the highly penetrant BRCA1 and BRCA2 genes account for the majority of families in whom disease-causal mutations have been identified. However, mutations in other genes have been associated with predisposition to breast or breast and ovarian cancer including (CHEK2, ATM, PALB2, RAD51C, RAD51D). Together these genes account for less than 20% of excess familial breast cancer risk and do not explain ~50% of high-risk families referred for genetic testing. This significant gap in our understanding of the genetic basis of breast cancer poses a significant barrier to our ability to identify women at increased risk, who would benefit greatly from appropriate clinical management. To identify additional breast cancer predisposition genes whole exome sequencing of familial high-risk breast cancer patients was undertaken. DNA samples from 50 pairs of breast cancer patients from high-risk breast cancer families with no pathogenic mutations in the BRCA1 or BRCA2 breast cancer predisposition genes were subjected to whole exome sequencing. The goal was to select candidate predisposition genes for further validation studies based on sharing of putative protein inactivating mutations among both members of each family and/or the frequency of inactivating mutations among the 50 families.

  Study phs000480

• Genome-Wide Association Study of Heparin-Induced Thrombocytopenia

  Heparin-induced thrombocytopenia (HIT) is an unpredictable, potentially catastrophic adverse effect resulting from an immune response to platelet factor 4 (PF4)/heparin complexes. We performed a genome-wide association study (GWAS) with positive functional assay as the outcome. Genetic associations were investigated in a cohort of functional assay-confirmed HIT cases, antibody-positive (function assay-negative) controls, and antibody negative controls. Both PF4-specific enzyme-linked immunosorbent assay (ELISA) and serotonin release assay (SRA) were positive in every HIT case. GWAS genotyping was performed at the Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences (IMS). All samples in the discovery and replication cohorts were genotyped using the lllumina® Infinium HumanOmniExpressExome BeadChip, which contains 958,497 markers, including 273,000 functional exonic markers. Quality control was accomplished using sample and marker call rate ≥98%, sex mismatch, duplicate concordance, and removal of related samples through identity by descent. Genomic imputation was performed for samples using Minimac4 and the phase3 v5 reference panel data from the 1000 genomes project. The primary GWAS analysis used multivariable logistic regression assuming an additive genetic model with functional assay-confirmed case status as the outcome. Both PF4/heparin antibody negative and antibody positive controls were considered controls in the primary analysis. Logistic regressions were used to generate odds ratios and 95% confidence intervals (95%CIs) after adjustment for age, sex, and first three principal components.

  Study phs002863

• Developing Allelic Imbalance Analysis from Single-Nucleus RNA-Seq Data

  Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool for understanding gene function across diverse cells. Recently, this has included the use of allele-specific expression (ASE) analysis to better understand how variation in the human genome affects RNA expression at the single-cell level. We reasoned that, because intronic reads are more prevalent in single-nucleus RNA-Seq (snRNA-Seq) and introns are under lower purifying selection, and are thus enriched for genetic variants, that snRNA-seq should facilitate single-cell analysis of ASE. Here we demonstrate how experimental and computational choices can improve the results of allelic imbalance analysis. We explore how experimental choices, such as RNA source, read length, sequencing depth, genotyping, etc., impact the power of ASE-based methods. We developed a new suite of computational tools to process and analyze scRNA-seq and snRNA-seq for ASE. As hypothesized, we extracted more ASE information from reads in intronic regions than those in exonic regions and show how read length can be set to increase power. Additionally, hybrid selection improved our power to detect allelic imbalance in genes of interest. We also explored methods to recover allele-specific isoform expression levels from both long- and short-read snRNA-seq. Overall, we provide an end-to-end experimental and computational approach for future studies.

  Study phs003749

• Heterogeneity in Lysosomal Storage Disorders

  Gaucher disease (GD) is an inherited lysosomal storage disorder caused by biallelic pathogenic variants in GBA1, which encodes glucocerebrosidase. Additionally, GBA1 variants are a well-established genetic risk factor for Parkinson's disease (PD), leading some PD research centers to incorporate GBA1 screening to identify patients who may benefit from targeted therapeutics. However, detecting GBA1 variants remains challenging due to the gene's high sequence homology with its pseudogene, which can give rise to complex recombinant alleles. This study evaluates the performance of Gauchian, a recently developed software tool for identifying GBA1 variants from whole genome sequencing (WGS) data. The assessment was conducted in a cohort of 90 individuals with GD and five GBA1 heterozygotes, all previously characterized through Sanger sequencing. While Gauchian successfully identified the most common genotypes, it demonstrated limitations in detecting rare or de novo variants due to its restricted internal database and heavy reliance on intergenic structural variants. These limitations led to misclassified homozygosity, incomplete genotyping, and undetected recombination events, ultimately reducing the tool's utility for comprehensive variant screening and precluding its application in diagnostic settings. The study dataset includes WGS from the 90 individuals used in the Gauchian pipeline. This data will be available through dbGaP to facilitate further research on GBA1 variant detection, genotype-phenotype correlations in GD and PD, and the development of improved bioinformatics tools for complex variant identification.

  Study phs003459

• The Federated EGA network

  In the last 10 years, most human omics data has been generated in the context of research consortia while recently there has been an emergence of large cohorts of human data generated by healthcare initiatives. Many countries in Europe now have nascent personalised medicine programmes. Thus, human genomics is shifting from being predominantly research-driven to being funded through healthcare systems. Genetic data generated in a healthcare context is subject to more stringent information governance than research data and nonetheless all data must adhere to national data protections laws. In this context, EGA identified the need for the development of a federated network to enable secure sharing of data whilst enabling genetic data to remain within the jurisdiction in which it was generated. The Federated EGA is designed to support national data management requirements for genomic and clinical data collected from citizens as part of healthcare or biomedical research projects. It includes a secure authorised access mechanism to support research use of these data across Europe and worldwide. We have engaged with over 14 ELIXIR countries to develop the federation model. The EGA federated configuration is composed of Central EGA, Federated EGA nodes and Community EGA nodes: Central EGA offers international submissions and helpdesk support, currently EGA co-managed by EMBL-EBI and CRG, Federated EGA nodes offer EGA services to researchers within their national jurisdiction, Community EGA nodes are individual institutions or initiatives with human genetic data intended to be shared with the research community. Key services available in the Federated EGA structure are: Central EGA Federated EGA node Community EGA nodes Data submission Offers international submissions service Offers submission service in a particular jurisdiction Does not offer an external submissions service Helpdesk support Provides external international helpdesk Provides helpdesk support for submitters in its jurisdiction and for approved users of data managed at its facilities Provides helpdesk support only for approved users of data managed at its facilities Data distribution Manages worldwide distribution for data hosted at Central EGA Manages worldwide distribution for data hosted at Federated EGA node Distribution for data hosted at Community EGA node EMBL-EBI and CRG have prepared a series of documents describing the overall governance and coordination framework. These describe the Federated EGA structure, the rights and responsibilities of the different parties and governing committees, and node operation guidelines. The federation governance proposal is under review by the first countries invited to join as Federated nodes, with further interested countries likely to join in the coming years. The Central EGA team has been working closely with many ELIXIR partners, including ELIXIR Finland, Luxembourg, Germany, Norway, Spain and Sweden.

  Blog the-federated-ega-network

• MRCA and MRCE SNP genotypes

  Gene expression levels can be an important link DNA between variation and phenotypic manifestations. Our previous map of global gene expression based on approximately 400K SNPs and 50K transcripts in 400 sib pairs from the MRCA family panel has been widely used to interpret the results of GWAS. Here, we more than double the size of our initial dataset with expression data on 550 additional individuals from the MRCE family panel using the Illumina whole genome expression array. We have used new statistical methods for dimension reduction to account for non-genetic effects in estimates of expression levels and we have also included SNPs imputed from the 1000 Genomes Project. Our methods reduced false discovery rates and increased the number of eQTLs mapped either locally or at a distance (i.e. in cis or trans) from 1,534 in the MRCA dataset to 4,452 (with <5% FDR). Imputation of 1000 Genomes SNPs further increased the number of eQTLs to 7,302. Using the same methods and imputed SNPs in the newly acquired MRCE dataset we identified eQTLs for 9000 genes. The combined results identify strong local and distant effects for transcripts from 14,177 genes. Our eQTL database (http://www.hsph.harvard.edu/faculty/liming-liang/software/eqtl/) based on these results is freely available to help define the function of disease-associated variants.

  Study EGAS00000000137

• Organoid BulkRNAseq

  Here, we aim to understand early determinants of brain organoid quality and generated a set of brain organoids from 12 different hPSC lines using an adaptation of the unguided Lancaster protocol (Lancaster & Knoblich, 2014). All cell lines were obtained from healthy donors. 12 donor hPSC lines were differentiated into brain organoids and a set of 72 individual organoids (6 per line) were randomly selected morphologically diverse organoids and subjected to bulk RNA sequencing for gene expression analysis. RNA was extracted using the RNeasy kit (Qiagen, Germany) according to the manufacturer’s instructions. A total of 1000 ng per sample was sent for RNA sequencing to Azenta Life Sciences (Genewiz Leipzig, Germany) for sequencing. Library preparation was performed using the NEBNext Ultra II RNA Library Prep Kit for Illumina following manufacturer’s instructions (NEB, Ipswich, MA, USA). mRNAs were first enriched with Oligo(dT) beads. The samples were sequenced using a 2x150 Pair-End (PE) configuration v1.5 at a depth of >20 million reads in each sample. Raw sequence data (.bcl files) generated from Illumina NovaSeq6000 was converted into fastq files and de-multiplexed using Illumina bcl2fastq program version 2.20. The raw sequence reads were aligned to the human reference genome GRCh38 using the STAR aligner (Dobin et al., 2013). Gene expression levels were quantified using the FeatureCounts tool (Liao et al., 2014).

  Study EGAS50000000659

• GENETIC HISTORY OF ITALY

  Recent scientific literature has highlighted the relevance of population genetic studies both for disease association-mapping in admixed populations and for understanding the history of human migrations. Deeper insight into the history of Italian population is critical for understanding the peopling of Europe. Because of its crucial position at the centre of the Mediterranean basin, the Italian peninsula has experienced a complex history of colonization and migration, whose genetic signatures are still present in contemporary Italians. In this study, we investigated genomic variation in the Italian population using 2.5 million single nucleotide polymorphisms (SNPs) in a sample of more than 300 unrelated Italian subjects with well-defined geographical origins. We combined several analytical approaches to interpret genome-wide data on 1,272 individuals from European, Middle Eastern, and North African populations. We detected three major ancestral components contributing different proportions across the Italian peninsula, and signatures of continuous gene flow within Italy, which has produced remarkable genetic variability among contemporary Italians. In addition, we have extracted novel details about the Italian population’s ancestry: we identified genetic signatures of major historical events in Europe and the Mediterranean basin from the Neolithic (e.g., peopling of Sardinia) to recent times (e.g., ‘barbarian invasion’ of Northern and Central Italy). These results are valuable for further genetic, epidemiological and forensic studies in Italy and in Europe.

  Study EGAS00001001458

• Automated system for scoring hematoxylin and eosin-stained ovarian cancer sections by identifying single cells uncovered that stromal cell ratio is a significant predictor for overall survival and progression-free survival.

  Concerted efforts in genomic studies have revealed profound insights in prognostic ovarian cancer subtypes. On the other hand, abundant histology slides have been generated to date, yet their uses remain very limited and largely qualitative. Our goal is to develop automated histology analysis as an alternative subtyping technology for ovarian cancer that is cost-efficient and do not rely on DNA quality. We develop an automated system for scoring hematoxylin and eosin-stained (H&amp;E) primary tumour sections of 91 late-stage ovarian cancer to identify single cells including cancer and stromal cells. We demonstrated high accuracy of our system based on expert pathologists’ scores (cancer=97.1%, stromal=89.1%) as well as compared to immunohistochemistry scoring (correlation=0.87). Quantitative stromal cell ratio is significantly associated with poor overall survival after controlling for clinical parameters including debulking status and age (multivariate analysis p=0.0021, HR=2.54, CI=1.40-4.60) and progression-free survival (multivariate analysis p=0.022, HR=1.75, CI=1.09–2.82). We demonstrate how automated image analysis enables objective quantification of microenvironmental composition of ovarian tumours. Our analysis reveals a strong effect of the tumour microenvironment on ovarian cancer progression and highlights the potential of therapeutic interventions that target the stromal compartment or cancer-stroma signalling in the stroma-high, late-stage ovarian cancer subset.

  Study EGAS00001001694

• UK10K NEURO ASD TAMPERE

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The Tampere Autism sample set consists of samples from Finnish subjects with ASD (autism spectrum disorders) with IQs over 70 recruited from a clinical centre for the diagnosis and treatment of children with ASD. For further information on this cohort please contact either Terho Lehtimaki (terho.lehtimaki@uta.fi) or Kaija Puura (kaija.puura@pshp.fi).

  Study EGAS00001000115

• Sensitive Monogenic Noninvasive Prenatal Diagnosis by Targeted Haplotyping

  During pregnancy, cell-free DNA (cfDNA) in maternal blood encompasses a small percentage of cell-free fetal DNA (cffDNA), an easilyaccessible source for determination of fetal disease status in risk families through non-invasive procedures. In case of monogenic heritabledisease, background maternal cfDNA prohibits direct observation of the maternally inherited allele. Non-invasive prenatal diagnostics(NIPD) of monogenic diseases therefore relies on parental haplotyping and statistical assessment of inherited alleles from cffDNA,techniques currently unavailable for routine clinical practice. Here, we present monogenic NIPD (MG-NIPD), which requires a bloodsample from both parents, for targeted locus amplification (TLA)-based phasing of heterozygous variants selectively at a gene of interest.Capture probes-based targeted sequencing of cfDNA from the pregnant mother and a tailored statistical analysis enables predicting fetalgene inheritance. MG-NIPD was validated for 18 pregnancies, focusing on CFTR, CYP21A2, and HBB. In all cases we could predict theinherited alleles with &gt;98% confidence, even at relatively early stages (8 weeks) of pregnancy. This prediction and the accuracy ofparental haplotyping was confirmed by sequencing of fetal material obtained by parallel invasive procedures. MG-NIPD is a robustmethod that requires standard instrumentation and can be implemented in any clinic to provide families carrying a severe monogenicdisease with a prenatal diagnostic test based on a simple blood draw.

  Study EGAS00001002622

• Homozygous loss-of-function variants in European cosmopolitan and isolate populations

  Homozygous loss of function (HLOF) variants provide a valuable window on gene function in humans, as well as an inventory of the human genes that are not essential for survival and reproduction. All humans carry at least a few HLOF variants, but the exact number of inactivated genes that can be tolerated is currently unknown-as are the phenotypic effects of losing function for most human genes. Here, we make use of 1432 whole exome sequences from five European populations to expand the catalogue of known human HLOF mutations; after stringent filtering of variants in our dataset, we identify a total of 173 HLOF mutations, 76 (44%) of which have not been observed previously. We find that population isolates are particularly well suited to surveys of novel HLOF genes because individuals in such populations carry extensive runs of homozygosity, which we show are enriched for novel, rare HLOF variants. Further, we make use of extensive phenotypic data to show that most HLOFs, ascertained in population-based samples, appear to have little detectable effect on the phenotype. On the contrary, we document several genes directly implicated in disease that seem to tolerate HLOF variants. Overall HLOF genes are enriched for olfactory receptor function and are expressed in testes more often than expected, consistent with reduced purifying selection and incipient pseudogenisation.

  Study EGAS00001001606

• scRNA-seq data of human nuclei collected from the temporal cortex of 17 individuals.

  Transcriptome analysis of single cells has tremendously increased our understanding of cellular heterogeneity in complex tissues. However, whole-cell transcriptomics cannot be applied to frozen tissue due to poor cell recovery after freezing. Human tissue is usually limited to tissue banks containing frozen material, and since single nuclei can be readily isolated from frozen tissues, human cell nuclei can substitute whole-cell analysis to extract single cell transcriptomes from human cells. Despite the importance of human tissue analysis, single-nucleus RNA-sequencing protocols are less developed than those for whole cells. SMARTSeq, either in form of custom-made SMARTSeq2 or as part of the Fluidigm C1 platform, provides a high resolution view of the transcriptome, has proven effective for whole-cell analysis and has recently been adapted to nuclei. Here, we show that the standard SMARTSeq2 protocol applied to single nuclei biases the amplification of single-nucleus transcriptomes due to unspecific capturing of transcripts, which can comprise the majority of reads in single-nucleus RNA-sequencing libraries. We demonstrate that modification of the SMARTSeq2 protocol with respect to template switching and cDNA amplification conditions generates sequencing libraries of higher complexity, allows for detection of more genes and reduces biases of the amplified transcriptome. In addition, modification of SMARTSeq2 chemistry allows for gene detection at shallower sequencing depth, thus increasing efficiency and decreasing cost.

  Study EGAS00001002882

• Uncovering tumor intrinsic and extrinsic factors that regulate hepatocellular carcinoma growth using patient derived xenograft assays

  Several major factors limit our understanding of hepatocellular carcinoma (HCC). First, human HCCs are infrequently biopsied for diagnosis and thus are not often biologically interrogated. Second, HCC initiation and progression are strongly influenced by the cirrhotic microenvironment, and the exact contributions of intrinsic and extrinsic tumor factors are unclear. A powerful approach to examine the personalized biology of liver cancers and the influence of host tissues is with patient derived xenograft (PDX) models. In Asia, HCCs from hepatitis B virus patients have been efficiently converted into PDXs, but few parallel efforts from the west have been reported. In a large-scale analysis, we implanted 93 HCCs and 8 cholangiocarcinomas (CCAs) to systematically analyze host factors and to define an optimized platform for PDX development from both surgical and biopsy samples. NSG mice that had undergone partial hepatectomy (PHx) represented the best combination of engraftability, growth, and passageability, but overall rates were low and indicative of a unique intrinsic biology for HCCs in the US. PDX models preserved the histology and genetic features of parental tumors, and ultimately, 9 new models were usable for pre-clinical studies. Intriguingly, HCC PDXs were differentially sensitive to regorafenib and sorafenib and CCA PDXs were also highly sensitive to regorafenib. PDX models functionalize early and advanced stage HCCs and revealed unique biological features of liver cancers from the US.

  Study EGAS00001004020

• Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target

  High-risk sarcomas, such as metastasized and relapsed Ewing and CIC-rearranged sarcomas, currently lack effective curative systemic treatment options. Precision medicine approaches offer hope and among them ex vivo drug response profiling of patient-derived tumor cells emerges as a promising novel tool to identify effective drugs for individual patients. Here, we established ex vivo culture conditions to propagate Ewing and CIC::DUX4-sarcomas as tumoroids in a co-clinical manner. These models retained their original molecular and functional characteristics, including recurrent ARID1A mutations, and serve as tumor avatars suitable for large-scale drug testing. Indeed, screening a large drug library on a small living biobank of such tumors not only revealed distinct response differences between the two entities, but also identified an exceptional dependency of CIC::DUX4-sarcoma cells on MCL1. Mechanistically. MCL1 was identified as a direct target gene of the CIC::DUX4 fusion protein. Genetic and pharmacological inhibition of MCL1 induced rapid apoptosis in CIC::DUX4-sarcoma cells and inhibited tumor growth in a xenograft model. Thus, MCL1 represents a potential novel therapeutic target for CIC::DUX4-sarcoma. Overall, our study highlights the feasibility of co-clinical drug response profiling for individual sarcoma cases and suggests that prospective tests, to evaluate its clinical benefit are highly warranted.

  Study EGAS00001008039

• Exome Chip Study of NIMH Controls

  Here, we report exome chip genotyping results of 1052 samples from the NIMH control set, a collection of healthy controls for general research use. The samples are all unrelated.

  Study phs000630

• DAC for EGA study: Multi-omic analyses from a randomized phase II study of epigenetic priming followed by nivolumab in previously treated metastatic non-small cell lung cancer

  This is the Data Access Committee for the EGA study: Multi-omic analyses from a randomized phase II study of epigenetic priming followed by nivolumab in previously treated metastatic non-small cell lung cancer (temp ID 800).

  Dac EGAC50000000563

• RGB TGCT Data Access Committee

  The RGB TGCT Data Access Committee is responsible for reviewing and approving requests for access to controlled genomic data generated from testicular germ cell tumor (TGCT) patients treated at the National Cancer Institute of Mexico (INCan). The committee evaluates requests to ensure that data use complies with the informed consent provided by participants and with applicable institutional and ethical regulations.

  Dac EGAC50000000959

• Genomewide Association Study of Inflammatory Bowel Disease

  WTCCC genome-wide case-control association study for Inflammatory Bowel Disease (IBD) using the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000006

• Saliva Microbiota of Finnish children from the PANIC study

  Saliva Microbiota of Finnish children aged between 6-8 yrs in the PANIC study. Baseline data. Studied for various lifestyle conditions and oral diseases (without caries/with caries).

  Study EGAS50000000708

• RNA-sequencing of ex situ stimulated donors blood cells

  Cells from whole blood stimulation assay were cryopreserved. The cryopreserved cells were thawed and subjected to RNA preparation. RNA obtained were subjected to for bulk sequencing.

  Study EGAS50000001077

• Tumor heterogeneity and immune-evasive microenvironment in T follicular helper cell lymphomas

  Single-cell analysis data for tumor and immune cells from lymph node and peripheral blood samples of 14 patients with T follicular helper cell lymphomas

  Study EGAS50000000275

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer - Biobank co-hort

  Liquid biopsies generated for minimal residual disease monitoring of advanced non-small cell lung cancer. Ultra deep targeted sequencing of lung cancer specific genes, with UMIs. This dataset consists of the biobank cohort

  Dataset EGAD50000002231

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer - DEDICATION co-hort

  Liquid biopsies generated for minimal residual disease monitoring of non-small cell lung cancer. Ultra deep targeted sequencing of lung cancer related genes with UMIs. This dataset contains the dedication cohort

  Dataset EGAD50000002230

• Raw scTCR-seq data for “Characterization of intestinal immune responses in generalized human and murine lipodystrophy”

  Raw 10X 5' v3 scTCR-seq data (TCR) for PBMC of 3 helthy donors and two AGLCD patient timepoints as well as of LPMC of 3 Crohns disease patients and one timepoint of the AGLCD patient.

  Dataset EGAD50000002191

• Raw scRNA-seq data for “Characterization of intestinal immune responses in generalized human and murine lipodystrophy”

  Raw 10X 5' v3 scRNA-seq data (GEX) for PBMC of 3 helthy donors and two AGLCD patient timepoints as well as of LPMC of 3 Crohns disease patients and one timepoint of the AGLCD patient.

  Dataset EGAD50000002190

• Sequencing dataset for the Predictive Endocrine ResistanCe Index (PERCI) in Breast Cancer cases

  Sequencing dataset for the Predictive Endocrine ResistanCe Index (PERCI) in Breast Cancer cases of the WSG-ADAPT trial (NCT01779206). The Oncomine Comprehensive v3 assay (ThermoFisher) and a customized amplicon-based NGS-Panel (DERv2) was performed.

  Dataset EGAD50000001595

• ERa ChIP-seq in breast healthy, primary cancer and metastatic tissues

  ChIP-seq has been perfomed on fresh-frozen tissue derived from healthy breast (HB), primary breast cancer (PB), BCa-derived liver metastasis (LM). Immunoprecipitation has been performed for ERa (sc-542, SantaCruz). Raw paired-end fastq.gz files are provided for both immunoprecipitated DNA and input samples.

  Dataset EGAD50000000642

• GBM Study Complete Raw Data

  Tumors from 173 GBM patients were analysed for somatic mutations to generate a personalized peptide vaccine targeting tumor-specific neoantigens. Exome libraries for 173 glioblastoma tumors and matched normal DNA were sequenced on Illumina platform, alongside total RNA from the tumors.

  Dataset EGAD50000000650

• Human TRIM24-MET fusion HGG RNA-seq

  Human RNA-seq data for TRIM24-MET fusion tumor primary samples and patient/PDOX-derived cell lines. Cells were treated with 0.1% DMSO or EC90 of MET inhibitors (capmatinib, cabozantinib, crizotinib) for 4 hours. BAM files containing aligned (and unaligned) reads to hg19 are provided.

  Dataset EGAD50000000194

• RNA-Seq data of S24 cells for the publication Recording physiological history of cells with chemical labeling.

  Recordings of elevated calcium levels allowed selections of cells from heterogenous populations for transcriptomic analysis. Paired RNA-Seq from S24 cells using Takara SMARTer Ultra Low Input RNA v4 kit and sequencing on a Illumina NovaSeq 6000.

  Dataset EGAD50000000082

• WGS dataset for gamma delta (γδ) T-ALL patients

  Whole genome sequencing data for 61 samples with acute lymphoblastic leukemia expressing the gamma delta T cell receptor (γδ T-ALL) and 29 germline samples

  Dataset EGAD50000000028

• Array data for oesophageal and related samples – sj_paper_methyl_tumour_release

  Array data for oesophageal and related samples – sj_paper_methyl_tumour_release

  Dataset EGAD00010001822

• Whole-exome sequencing and microRNA profiling predicted relapse risk of stage I lung adenocarcinomas for the study and all the datasets.

  This dataset contains CEL files and rma normalized expression value for microarray of stage I lung adenocarcinomas from Asian patients. In total, there are 69 patients and 138 samples, including 69 tumor samples and 69 adjacent normal samples.

  Dataset EGAD00010001901

• Dataset Rdata segmentations

  This data set contains an .Rdata file for all the processed segmentation profiles from 81 lpWGS samples included used in downstream analyses from Github repository Evo_history_CACRC. Lastly, there is an .Rdata object with 50 segmentations for 50 total samples from 25 sporadic SNP adenomas used in the comparison with colitis samples.

  Dataset EGAD00010001586

• Chromatin_Profiling_in_Twins

  50 lymphoblastoid cell lines of adult female Twins which are part of the MuTHER study, subjected to Chromatin Immunoprecipitation using an antibody for H3K4me1. H3K4me1 peaks mark distal regulatory elements.

  Study EGAS00001000098

• S_CORT_Stratification_in_COloRecTal_cancer_

  Colorectal cancer samples will be submitted for Illumina sequencing using a custom capture of 116 genes implicated in colorectal tumourigenesis. Driver mutations will be detected and ultimately correlated with phenotypic data.

  Study EGAS00001001521

• Myeloma_Targeted_Follow_up_Study

  390 samples, perform WGA, and send the WGA’d DNA to core for pre-capture library and tagging, pulldown with ELID 631172 (16 samples per reaction tube), and sequencing (24 samples per lane)

  Study EGAS00001000880

• Organoid_Derivation_Pilot__RNAseq

  Generation of normal and cancer organoids for sequencing as part of the WTSI-CRUK international collaboration with NCI (in HCMI) to generate the next generation of cancer cell lines.

  Study EGAS00001002223

• Patient-derived conditionally reprogrammed cells (CRCs) were established and characterized to assess their biological properties and to apply these to test the efficacies of drugs.

  RNA seq data was used for the characterization and profiling of the created patient-derived cells and in vivo tissue.

  Study EGAS00001001702

• BIG_MS_Pilot

  Testing logistics and infrastructure of molecular screening program. Core biopsies taken from invasive recurrent or metastatic breast cancer to evaluate and identify molecular traits rendering them suitable for clinical trials

  Study EGAS00001000616

• SureTypeSC - accurate genotyping of single-cell SNP array data

  We used a collection of single cells from two Coriell cell lines to train and validate a machine learning method for quality assessment of the single cell genotypes

  Study EGAS00001004621

• Organoid_Derivation_Project__WGS

  Generation of normal and cancer organoids for sequencing as part of the WTSI-CRUK international collaboration with NCI (in HCMI) to generate the next generation of cancer cell lines

  Study EGAS00001002222

• Epi2Diag raw methylation array data for patients with neurodevelopmental disorders

  Raw methylation array data (Illumina Infinium EPIC v2.0) from patients with rare neurodevelopmental disorders. IDAT files were generated from DNA extracted from whole blood at the ASGARD platform, Inserm U1245, Univ Rouen, CHU Rouen, to investigate new episignatures and provide independent validation datasets for existing episignatures.

  Dataset EGAD00010002724

• Characterization of iPSC derived macrophages - cardiovascular pilot (2017-05-24)

  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 2017-05-24.

  Dataset EGAD00001003347

• WES fastq files of IPDGC UK cohort

  As part of the International Parkinson's Disease Genomics Consortium, exomes of Parkinson's disease (PD) patients and healthy controls were sequenced to study the genetic etiology of PD. This UK cohort consists of 70 PD patients. Researchers can apply for access to fastq files for this cohort.

  Dataset EGAD00001003096

• Next generation sequencing of liver cancer cell lines

  Whole genome sequencing was performed for 81 liver cancer cell lines. Additional whole exome sequencing was performed for a subset of 11 liver cancer cell lines. SK_HEP_1 was also provided, though considered not hepatic origin. These sequencing data provided the detailed genomic characterization of liver cancer models.

  Dataset EGAD00001003165

• Transcriptome (RNA-seq) data for the validation of the glioblastoma progression study (GBMatch).

  37 transcriptomes derived from fresh-frozen glioblastoma tumor samples. These transcriptomes have been produced for validation purposes and match the corresponding RRBS and WGS profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004076

• Genomic (WGS) data for the validation of the glioblastoma progression study (GBMatch).

  43 low-coverage genomes derived from fresh-frozen glioblastoma tumor samples. These genomes have been produced for validation purposes and match the corresponding RRBS and RNA-seq profiles in that DNA and RNA was extracted from the same tumor samples.

  Dataset EGAD00001004077

• Genomic profiling of well-differentiated and dedifferentiated liposarcoma from the same patient

  Well-differentiated, dedifferentiated, and matched normal tissues from liposarcoma (51 specimens) from 17 patients were obtained for whole exome sequencing. Tumors were submitted from 9 patients were used for RNA sequencing. The bam files are made available in this dataset.

  Dataset EGAD00001003976

• WGS files for Mullighan PAX5_B-ALL

  WGS files for Mullighan PAX5_B-ALL paper titled "PAX5-driven Subtypes of B-cell Acute Lymphoblastic Leukemia"

  Dataset EGAD00001004446

• WES files for Mullighan PAX5_B-ALL

  WES files for Mullighan PAX5_B-ALL paper titled "PAX5-driven Subtypes of B-cell Acute Lymphoblastic Leukemia"

  Dataset EGAD00001004447

• Colon adenomas and adenocarcinomas and matched mucosae

  Whole exome sequencing in sporadic colorectal cancers (CRC) and advanced adenomas (Ad-As), and their paired healthy mucosa, for a deeper understanding of the biology of this cancer.

  Study EGAS00001007255

• RNA-seq of CD34+ HSPCs from LRMDS patients

  To profile transcriptional alterations of HSPCs in LR-MDS patients, 7AAD−CD45+Lin-CD235a−CD34+ cells were isolated from healthy donors and LR-MDS patients for RNA sequencing.

  Study EGAS00001008182

• Targeted_NanoSeq_Sperm

  Targeted NanoSeq in sperm samples provided by healthy patients. A custom-designed panel of ~200 genes will be used to achieve high depth coverage (aiming for ~1000X at panel sites).

  Study EGAS00001005920

• Diffuse Intrinsic Pontine Glioma

  This study contains DNA and RNA sequencing data for 5 DIPG patients. All patients have tumor DNA data, 4 have matched normal DNA data and 3 have tumor RNA seq data

  Study EGAS00001006353

• Prediction of HLA genotypes using NGS data

  High-precision human leukocyte antigen (HLA) genotyping is crucial for anti-cancer immunotherapy, but existing tools predicting HLA genotypes using next-generation sequencing (NGS) data are insufficiently accurate.

  Study EGAS00001005274

• Microinjection of hIPSC-derived intestinal organoids with Salmonella Typhimurium

  To generate an RNA-Seq dataset for organoids apically stimulated with Salmonella Typhimurium.These data are 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/

  Dataset EGAD00001001363

• BLUEPRINT release August 2015, RNA-Seq for Multiple myeloma, on genome GRCh38

  RNA-Seq data for 11 Multiple myeloma sample(s). 11 run(s), 11 experiment(s), 11 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001471

• BLUEPRINT release January 2015, DNase-Hypersensitivity for inflammatory macrophage

  DNase-Hypersensitivity data for 2 inflammatory macrophage sample(s). 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

  Dataset EGAD00001001193

• BLUEPRINT release August 2015, RNA-Seq for monocyte, on genome GRCh38

  RNA-Seq data for 4 monocyte sample(s). 4 run(s), 4 experiment(s), 4 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_rnaseq_analysis_crg_20150820

  Dataset EGAD00001001572

• BLUEPRINT: RNA-seq for monocytes and neutrophils

  RNA-seq for monocytes and neutrophils

  Dataset EGAD00001000675

• BLUEPRINT: ChIP-seq for monocytes &amp; neutrophils

  ChIP-seq for monocytes and neutrophils

  Dataset EGAD00001000676

• BLUEPRINT release August 2014, DNase-Hypersensitivity for inflammatory macrophage

  DNase-Hypersensitivity data for 2 inflammatory macrophage sample(s). 2 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

  Dataset EGAD00001000926

• BLUEPRINT release August 2016, DNase-Hypersensitivity for macrophage - T=6days untreated, on genome GRCh38

  DNase-Hypersensitivity data for 4 macrophage - T=6days untreated sample(s). 6 run(s), 4 experiment(s), 4 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002398

• BLUEPRINT release August 2016, DNase-Hypersensitivity for monocyte - T=0days, on genome GRCh38

  DNase-Hypersensitivity data for 2 monocyte - T=0days sample(s). 4 run(s), 2 experiment(s), 2 analysis(s) on human genome GRCh38. Part of BLUEPRINT release August 2016. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20160816/homo_sapiens/README_dnaseseq_analysis_20160816

  Dataset EGAD00001002300