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• Immunoglobulin Heavy-Chain locus in Multiple Sclerosis (n=4)

  Peripheral-blood or monocyte DNA from two healthy donors and two individuals with multiple sclerosis were sequenced on a PromethION-2 Solo (P2 Solo) instrument using R10.4.1 flow-cells and the Ultra-Long DNA Sequencing Kit (SQK-ULK114). For each participant we provide FASTQ reads (on-target), and haplotype-resolved assemblies of the complete IGH locus (~1.3 Mb) in FASTA format.

  Dataset EGAD50000001517

• WGS dataset for Multimodal antigenic escape to GPRC5D-targeted T-cell engagers in multiple myeloma

  We analyzed the genome of plasma cells collected from bone marrow samples or plasmocytoma from patients prior to (when available) and progression on anti-GPRC5D T cell engagers. Dataset includes tumor and matched normal WGS data aligned to GRCh38.p14 in bam format, as well as tumor small variant and CNV calls.

  Dataset EGAD50000001643

• TenK10K Phase 1: Whole Genome Sequencing tandem repeats multi-sample VCFs

  Tandem repeat variants were called for 1,925 samples from phase 1 of the TenK10K project. Variant calling from WGS alignments to the GRCh38 reference assembly was completed with ExpansionHunter v5. This dataset is comprised of autosomal tandem repeat variants provided as multisample compressed VCF format files. SNV-derived principal component scores used in the manuscript (Tanudisastro et al.) are also provided in this dataset.

  Dataset EGAD50000002378

• IGPP Consortium GWSS Summary Results Data

  The data are the aggregate results from an IGPP Consortium genome-wide survival study, showing overall risk for Parkinson disease progression associated with each variant in a longitudinal cohort study. 11.2 million deeply imputed variants in 3,821 PD patients who were prospectively tracked with 36,123 visits over a median of 6.7 years from disease onset (inter-quartile range, 4.2 years) were analyzed. Data include hazard ratio, SNP ID, and P value.

  Dataset EGAD00001007060

• Tumor/Normal WXS and RNASeq from patients dosed with neoTCR T-cell therapy

  Sixteen patients with refractory solid cancers received up to three distinct neoTCR-transgenic cell products, each expressing a patient-specific neoTCR, in a cell dose-escalation, first-in-human phase 1 clinical trial (NCT03970382). Included are the tumor and normal WXS and tumor RNAseq for dosed patients.

  Dataset EGAD00001009830

• Exome sequencing reveals pathogenic variants in known and novel candidate genes for severe sperm motility disorders.

  The dataset is composed by the raw and processed sequencing data generated from 8 Australian Patients and 13 Argentinian Patients affected by a form of male infertility characterised by vital, but immotile sperm often in combination with a spectrum of structural abnormalities of the sperm flagellum.

  Dataset EGAD00001007085

• Targeted sequencing of candidate genes in calcific aortic valve stenosis (2019-08-21)

  The objective is to identify new disease genes involved in calcific aortic valve stenosis (CAVS) by screening newly identified candidate genes. The recruitment of patients with CAVS has been achieved by l’institut du thorax (Nantes, France). DNA from the selected patients has been analysed by targeted capture (Agilent SureSelect) and massively parallel sequencing (Illumina). . This dataset contains all the data available for this study on 2019-08-21.

  Dataset EGAD00001005275

• Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

  The dataset for Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer includes 106 bam files from whole exome next-generation sequencing on the Illumina HiSeq2500. The samples analyzed include matched tumor/normal samples from non-small cell lung cancer patients treated with immunotherapy.

  Dataset EGAD00001005796

• Targeted DNA sequencing dataset for the study "Molecular profiling of EBV associated diffuse large B-cell lymphoma"

  We performed deep targeted DNA sequencing with a panel of 74 selected cancer-related genes previously identified to be recurrently mutated in EBV associated DLBCL. Sequencing was performed on a HiSeq platform (Illumina) with 250 bp paired-end reads. There are 68 FFPE samples in this targetedDNAseq-dataset with 46 unpaired tumors and 22 normals used as a panel of normals.

  Dataset EGAD00001009396

• Circular RNA characterization in functionally distinct brain regions

  RNA extracted from middle temporal gyrus (MG) brain region of healthy elderly controls. Three pairs of samples were generated, each pair consisting of one sample that was enriched for circular RNAs using RNase R, and a second sample that was not enriched (total N=6). Remaining samples in the study from other functionally distinct brain regions are currently under process and will be released soon.

  Dataset EGAD00001004211

• oncogenic gene fusions in primary colon cancers

  This dataset represents RNA-sequencing data from 278 primary colon cancers obtained from fresh-frozen tumor sections. RNA-sequencing was performed using TruSeq library preparation and samples were sequenced on Illumina NextSeq and HiSeq. The data are available as Illumina NextSeq and HiSeq fastq files (_R1.fastq and _R2.fastq for each tumor sample, 556 files in total).

  Dataset EGAD00001003291

• Clonal cultures of T memory cells

  Sequence data (bam files) of two RRBS samples for paper "A comprehensive analysis of 195 DNA methylomes reveals shared and cell specific features of partially methylated domains". Short Description: CD4+ T memory cells (CD3+ CD4+ CD45RA- CD45RO+ CD25-) from donors were sorted by flow-cytometry either as a bulk culture ('ex vivo' sample) or in a single-cell format into 96 well-plates ('clone' sample) in the presence of a TCR stimulus.

  Dataset EGAD00001004303

• Transcriptome sequencing of myelodysplasia

  Transcriptome sequencing was performed on 214 patients with myelodysplasia in this study. RNA was obtained from bone marrow CD34+ cells (n=100) and/or bone marrow mononuclear cells (n=165). Transcriptome sequencing was performed for both cell fractions in 51 patients. A total of 211 patients were genotyped by targeted deep sequencing. We also studied bone marrow CD34+ cells and bone marrow mononuclear cells obtained from three healthy adults each.

  Dataset EGAD00001003891

• WES analysis of patients with USP8 wild-type corticotroph adenomas

  The overall goal of the Identification of recurrent mutations in Cushing’s disease project is to study the impact of whole-exome sequencing (WES) on the clinical care of cancer patients and oncology provider practices. The aims of Project are to implement and establish the feasibility of WES in patients with USP8 wild-type corticotroph adenomas; to develop a framework for the understanding of the molecular mechanism of the pathogenesis of corticotroph adenoma.

  Dataset EGAD00001004136

• EORTC study on the evolution of driver mutations and MGMT promotor methylation in glioblastomas treated with standard of care: Correlation with survival and impact on trial design

  Precision medicine trials in glioblastoma should be conducted at tumor recurrence. However, second surgery for recurrent GBMs is not routinely performed and therefore molecular data is predominantly derived from primary samples. This study aims to establish the frequency of driver changes at tumor recurrence.

  Dataset EGAD00001004593

• Lymphocyte LCM WGS (2020-02-20)

  Using whole genome sequencing of lymphocytes excised from human tissue using laser capture microscopy (LCM), we identify the mutations arising in these microenvironments. This work will contribute towards developing a catalogue of mutations present in tissue resident lymphocytes across a range of tissues, and will characterize the mutational signatures that result from each microenvironment. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005992

• CRC cell line ChIP-seq

  ChIP-Seq data for CTCF, H3K4me1, H3K4me3, H3K27ac, H3K27me3, H3K36me3 in C32, CL11, HT29, SW403, SW480, SW948 MSS CRC cell lines

  Dataset EGAD50000000295

• Whole exome sequencing of two BPDCN patients for tracing clonal evolution

  Whole exome sequencing data was mapped to GRCh38 using bwa-mem2 as implemented in the nfcore sarek workflow.

  Dataset EGAD50000000309

• ATAC_TPO3_2023

  Human engineered CRC organoids (APC KO; KRAS G12D; TP53 KO) were grown in glucose, lactate or with DCA . Samples were collected and processed for bulk ATAC-seq.

  Dataset EGAD50000000088

• COVID-19 Exome Sequencing DAC policy

  This is the DAC policy for exome sequencing data from COVID-19 patients from EASI genomics and NIMgentics and belonging to the study "Variability in immune response genes and prediction of severe SARS-CoV-2 infection(INMUNGEN-Cov2 project)"

  Dac EGAC50000000065

• Khoe-San whole genome sequencing

  High-coverage (>30X) whole genome data (FASTQ) for 25 southern African Khoe-San individuals (from five populations). These are the same individuals as in Schlebusch et al. 2020 (EGAD00001006183), but different data.

  Dataset EGAD50000001559

• HiChIP for 2 samples

  This dataset contains H3K27ac HiChIP data from ta primary sample and a patient derived model (PDX) of the novel FOXF1/FENDRR ALL subtype. All the 2 samples are in bam file type.

  Dataset EGAD50000001787

• eFORGE software tool BLUEPRINT dataset

  DNase accessibility data for BLUEPRINT consortium immune cells included in eFORGE software tool

  Dataset EGAD00001002713

• Dataset for Stromal-induced epithelial-mesenchymal transition induces drug resistance in acute lymphoblastic leukemia

  RNA-seq was performed to compare gene expression profiles between 11 patient adherent ALL samples and nonadherent ALL samples.

  Dataset EGAD00001009056

• Genomic determination for Homologous Recombination Deficiency (HRD) by shallow Whole Genome Sequencing (sWGS)

  Homologous recombination deficiency (HRD) score in a large cohort of 55 triple-negative breast cancer PDX

  Dataset EGAD00001008839

• IL2 data set including 59 samples

  The dataset is referenced by EGA Study ID EGAS00001003605, which includes the short-reads data for 59 samples. All short-reads data files are in fastq format.

  Dataset EGAD00001004967

• RNA sequencing of 20 intra/extra hepatic bileduct organiods

  This dataset contains RNA sequencing data for 20 intra/extra hepatic bileduct organiods. Data is in BAM format and was processed by STAR.

  Dataset EGAD00001005225

• Whole Genome Sequencing of Normal Singaporean Volunteers

  Whole-genome sequencing (WGS) data for 546 Singaporean volunteers used to estimate WGS-LTL in the study. Samples were sequenced using Illumina Hiseq X to a mean coverage of 30X.

  Dataset EGAD00001005480

• Whole Exome Data for two affected individuals in a family with severe congenital neutropenia (SCN).

  Raw Whole Exome Sequencing data from Blood samples drawn from related Female participants presenting severe congenital neutropenia.

  Dataset EGAD00001005937

• TSG knock-out in hiPSCs (2017-08-10)

  We will perform RNAseq to evaluate the effects of the loss of a list of TSGs on the transcriptome. This dataset contains all the data available for this study on 2017-08-10.

  Dataset EGAD00001003556

• ChIP-seq for GOF p53

  This dataset includes ChIP-seq data from two cell lines (HKCI-11 (GOFp53) and MIHA(WT p53)). All the experiments were performed on Illumina HiSeq 2000 platform with raw reads stored in fastq format.

  Dataset EGAD00001005449

• Therapeutic vulnerabilities in the DNA damage response for the treatment of ATRX mutant neuroblastoma

  Whole genome sequencing data of isogenic ATRX/TP53 knockout clones of the neuroblastoma cell line SK-N-SH

  Dataset EGAD00001006294

• Spatially resolved cellular and molecular drivers of cardiac remodelling in healthy and failing human hearts: Adult Spatial (2025-07-31)

  Spatial transcriptome analysis of the human heart . This dataset contains all the data available for this study on 2025-07-31.

  Dataset EGAD00001015666

• MP2PRT: Evaluation of an Inflammation Polygenic Risk Score (iPRS) to Predict Cancer Related Cognitive Impairment and Fatigue in Patients Receiving Chemotherapy for Non-Metastatic Breast Cancer in URCC0701 and URCC10055

  This study is a secondary analysis of cancer related cognitive impairment (CRCI) and cancer related fatigue (CRF) among participants in URCC0701 and URCC10055 from the University of Rochester NCI Community Oncology Research Program (NCORP) Research Base. CRCI and CRF are common, troublesome, and dose-limiting toxicities reported by patients undergoing breast cancer chemotherapy that have an etiologic basis linked to low-grade systemic inflammation. Chronic, low-grade systemic inflammation is, in part, genetically determined with common single nucleotide polymorphisms (SNPs) capturing variation across individuals. This study aimed to 1) determine whether an inflammation polygenic risk score (iPRS) is associated with CRCI or CRF, 2) determine whether the relationship between the iPRS and CRCI or CRF is modified by exercise at the time of cancer treatment, 3) identify SNPs associated with serum cytokines measured at the time of cancer treatment, and 4) identify novel CRCI- and CRF-associated risk SNPs via genome-wide association analyses. We found that there was a significant inverse correlation between the iPRS and change in fatigue score from pre-chemotherapy to post-chemotherapy while there was no statistically significant association between the iPRS and cognitive impairment score. The inverse relationship between the iPRS and fatigue may be explained in part by the finding that the iPRS was also significantly associated with greater pre-chemotherapy fatigue, suggesting that women with a genetic predisposition to low-grade systemic inflammation (i.e., high iPRS) have more fatigue at the time of breast cancer diagnosis and, therefore, are less likely to worsen over the course of treatment. In contrast, women with a low iPRS had significantly less fatigue pre-chemotherapy and a significant worsening of fatigue from pre- to post-chemotherapy. The relationship between the iPRS and fatigue remained after adjustment for patient and cancer treatment covariates and was most pronounced in women who reported regularly exercising for at least 6 months prior to starting their cancer treatment. Exploratory genome-wide analysis identified a novel risk locus on chromosome chr6q27, tagged by rs9365961, associated with CRCI. This locus is upstream of TBXT, which encodes an embryonic nuclear transcription factor previously associated with susceptibility to neural tube defects. The genome-wide SNP data, patient-reported CRCI and CRF outcome measures, and covariate data used in this analysis are available through dbGaP.

  Study phs003688

• How upcycled prostate cancer sequences enabled key findings on telomeres length

  The length of telomeres, the chromosomes’ end tails, as depicted in the figure below, physiologically shorten with aging. This means that younger cells have longer telomeres compared to their aged counterparts; one could say that the length of cells’ telomeres is a measure of their replicative power. Cancer cells are known to be able to turn this into their favour, and expand their replicative immortality through telomere lengthening and maintenance. Despite being a well-studied pan-cancer hallmark, the relation of the telomeres length to specific cancer genomic features is poorly understood. Julia Livingstone and her colleagues from P.C. Boutros' team in Los Angeles focused their work on prostate cancer. To investigate the relations between telomere length and the clinico-genomics of prostate tumours, they used whole genome sequencing (WGS) of 392 published tumour–reference pairs previously deposited at the EGA under accession numbers EGAS00001000400 and EGAS00001000900. Their work was published on Nature Communications in November 2021. They determined the telomere length of the sequencing sample, from both tumour and non-tumour adjacent tissues, and subsequently ran statistical analysis to investigate possible correlation between the telomeres length with several cancer features. The team discovered that telomeres length does not correlate with any specific driver gene mutation, but it does with the overall frequency of single nucleotides variants in a sample. This finding suggests that tumours with shorter telomeres accumulate more mutations without strong selective pressures for specific ones. While proliferation rate did not correlate directly with telomere length, methylation of almost half of all genes strongly did. The team’s results are massive and reveal a complicated and fascinating relation of different clinical and genomic features of prostate cancer with telomere length. In the paper discussion, they smartly consider different possibilities. As noted above, all these amazing results have been obtained analysing previously sequenced samples. Remarkably, the researchers who generated the samples did not focus at all on telomeres length. They indeed studied specific genes mutations and the features of early and late-onset prostate cancer. This proves, once again, the power of sequencing data re-use. This data is tremendously rich in information, and can hardly be exhausted with any number of analyses. Generating sequencing data, especially Whole Genome Sequencing, even better if tumor-reference paired, is like shopping every last article at the grocery store. You can then cook several recipes, or prepare a seven-course dinner, and still have ingredients left for someone else to borrow and cook something you have not thought about, a recipe that is just not in your cookbook. Noteworthy, the data retrieved from the EGA for this paper is associated with rich and complete metadata, meaning pheno-clinical information regarding the sample donors. As Julia Livingstone and her team wrote, using rich clinical annotations enabled them to assess the relationship between telomere length and patients outcome. This highlights once again the importance of reporting and annotating metadata correctly; It might feel like extra work for the researchers depositing their data, but it really has a huge value. Our team at the EGA is currently working to improve the metadata annotation process, with the aim to maximize the benefits for the scientific community.

  Blog prostate-cancer-sequences-enabled-key-findings-on-telomeres-length

• PCPT and SELECT Cohorts: Core Infrastructure Support for Cancer Research

  SELECT study: SELECT was a phase III, double-blind, placebo-controlled 4-arm study of selenium, vitamin E, selenium and vitamin E together, and placebo designed to assess the effect of these supplements on the incidence of prostate cancer. Funded by the National Cancer Institute and conducted by SWOG, the study opened in August 2001 and quickly exceeded its accrual goal of 35,533 men.In the fall of 2008, the trial's Data Safety and Monitoring Committee recommended that participants discontinue taking study supplements due to convincing evidence (planned interim futility analysis) that neither vitamin E nor selenium supplements were associated with the prevention of prostate cancer. A subsequent analysis in 2011 showed a significant 17% increase in prostate cancer incidence in participants who were on the vitamin E only arm. Approximately 17,000 participants from the original trial recently completed an additional four years of centralized follow-up. This follow-up ended on May 31, 2014 and SELECT is now closed. PCPT study: The Prostate Cancer Prevention Trial (PCPT) was a SWOG Cancer Research Network-coordinated study designed to test whether the drug finasteride (Proscar®) would prevent prostate cancer in men ages 55 and older. This study was closed on June 24, 2003 because the study objective had been reached. The results of the study, which did find a preventive benefit for the drug, were published as "The Influence of Finasteride on the Development of Prostate Cancer," in the New England Journal of Medicine on July 17, 2003.

  Study phs003382

• The Finland-United States Investigation of NIDDM Genetics (FUSION) Study - Islet Expression and Regulation by RNAseq and ATACseq

  This study evaluates gene expression and its regulation in human pancreatic islets, a tissue relevant in the study of genetic risk factors contributing to diabetes. We obtained pancreatic tissue sections and purified pancreatic islets from deceased donors and processed these biological samples to generate various data types. We generated spatial transcriptomic data from pancreatic tissue samples using the 10X Genomics VISIUM technology with sequencing on the Illumina NovaSeq platform. We also generated multiple data types from the purified pancreatic islets using genome-wide SNP chips, bulk RNA-Seq, microRNA (miRNA)-Seq, whole genome sequence, DNA methylation (methyl)-Seq, cap analysis of gene expression (CAGE)-Seq, single cell RNA-seq, and single nuclei ATAC-seq approaches. These data include ATAC-seq of two islet subjects, RNA-seq of 31 additional subjects, genome-wide chip genotypes, and imputed genotypes of the 33 subjects released with phs001188.v1. For genotyping, 500-1000 islet equivalents (IEQ) were cultured as in Gershengorn (Science, 2004, PMID: 15564314); genomic DNA isolated from islet cultures. For RNA analyses, 2500-5000 IEQ from each islet source were used for bulk or single-cell RNA isolation. Messenger RNA was isolated with trizol extraction and 12-plex libraries were generated using the Illumina TruSeq directional mRNA-seq library protocol. Bulk RNA sequencing was performed on HiSeq2000/HiSeq2500/Hiseq4000/NovaSeq6000 sequencers using paired-end reads at the NIH Intramural Sequencing Center (NISC). miRNA libraries were prepared from total RNA from 68 samples, pooled and sequenced 50bp single-end reads on Illumina HiSeq2500. CAGE libraries were prepared from total RNA samples using the nAnT-iCAGE protocol at DNAFORM, Japan. CAGE libraries were sequenced at the NIH Intramural Sequencing Center (NISC) on the HiSeq2000 sequencer. Genotyping on the Illumina Omni2.5M array was performed at the NHGRI Genomics Core facility. Genotypes were imputed using the HRC.r1.1.2016 reference panel. To assess regions of open chromatin in islets, we performed bulk ATAC-seq on HiSeq2000 sequencers using paired-end reads at NISC. Single-nuclei ATAC-seq libraries were prepared using single-cell-combinatorial-indexing (sci-) ATAC-seq protocol and sequenced on Illumina NextSeq using paired-end reads. scRNA-seq libraries were generated using the 10X Genomics platform and sequenced on Illumina HiSeq3000 at the Genomics Technology Core of the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS). Greater than 90% of the loci associated with T2D through genome-wide association studies occur in non-coding regions, suggesting a strong regulatory component to disease susceptibility. Therefore, there is a critical need to understand the full spectrum of genetic variation and regulatory element usage in T2D-relevant tissues. To that end, this study contains multiple genomic and transcriptomic data sets from pancreas tissue sections and pancreatic islets, a resource that will contribute to our efforts to investigate the genetic risk factors for type 2 diabetes.

  Study phs001188

• Population Genetic Testing and SERPINA1 Sequencing Identifies Unidentified Alpha-1 Antitrypsin Deficiency Alleles and Gene-Environment Interaction with Hepatitis C Infection

  Design and aims: Data were available through an institutional effort to combine de-identified electronic health records (EHR) data with genomic information from a DNA biobank. The design of this work was a retrospective cohort study in which we investigated the rates of liver transplantation and hepatitis C infection as it relates to genotype risk for alpha-1 antitrypsin deficiency (AATD). We used regression analysis to look for relationships between these risks and outcomes. This led to further investigation of environmental exposures and phenotypes as it related to the underlying genotypic risk. Population information: The cohort consisted of 72,027 individuals of European ancestry for whom genotype and EHR data were available. Molecular technologies employed: Genome-wide genotyping was previously performed using the Illumina Infinium Expanded Multi-Ethnic Genotyping Array plus custom content (referred to as the Vanderbilt University Medical Center BioVU MEGAEX). Individuals' AATD-related alleles were inferred from the genotyping data. Principal findings of the study: Liver transplantation was associated with presence of the Z AATD allele and with hepatitis C infection. There was a significant interaction between AATD genotype groups and hepatitis C infection as it related to liver transplantation. Data available through dbGaP: Inferred AATD genotype status, sex, age, length of EHR in years, presence/absence of AATD clinical diagnosis, liver transplant status, and hepatitis C infection status.

  Study phs003297

• Aurora US Metastatic Breast Cancer Retrospective Project

  The AURORA US Metastatic Breast Cancer project is funded by the Breast Cancer Research Foundation (BCRF) Evelyn H. Lauder Founder's Fund for Metastatic Breast Cancer Research. This multi-center effort conducted within the Translational Breast Cancer Research Consortium (TBCRC) and cancer researchers to better understand the metastatic process through the study of both the primary and metastatic tissue. In the retrospective phase, TBCRC sites submitted matched primary and metastatic tissues and blood from previous collections for piloting the process. Samples were profiled using whole genome DNA sequencing, whole exome DNA sequencing, DNA methylation arrays, and RNA sequencing. The final freeze set for samples with successful nucleic acid extraction and molecular assays included 55 patients with 31 primary tissues and 102 metastases. Twenty patients had tissue collected at autopsy and included 19 with more than one metastasis. Metastases were from 20 different tissue locations with the most common sites being liver, lung, lymph node, and brain. The median age at primary diagnosis was 49 years. The clinical subtypes of the primary tumors were 34% Triple Negative, 30% ER+HER2-, 11% ER+HER2+, and 7% ER-HER2+. Patients received an average of 3 lines of therapy in the metastatic setting. The median overall survival from primary diagnosis was 4.5 years and overall survival from metastatic diagnosis was 2 years.

  Study phs002622

• Clinical Study of Intermittent Positive Pressure Breathing (IPPB-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To evaluate the efficacy of long-term intermittent positive pressure breathing (IPPB) treatment when used as an adjunct to the overall care of ambulatory outpatients with chronic obstructive pulmonary disease. The evaluation compared the use of IPPB with use of a powered nebulizer.Participants: A total of 3218 participants were enrolled.Design: Multicenter randomized controlled clinical trial. Conclusions: Compliance with treatment, lung function, and quality of life were evaluated at regular intervals during follow-up, and records were kept of hospitalizations and vital status. Treatment compliance was less than optimal; only half of the participants used their devices for the prescribed amount of time or 10 minutes at least three times a day. Although this was disappointing, it was probably the best compliance that could be attained. There was no statistically significant difference between the treatment groups in mortality, rate and duration of hospitalizations, or change in lung function or life quality with time, overall or for clinically relevant subgroups. The trial group saw no advantage of IPPB over compressor nebulizer therapy and concluded that, if an advantage existed, it must be marginal.

  Study phs004010

• National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS)

  NIAGADS is an NIH controlled-access data repository that collaborates with researchers around the world to facilitate data access and sharing for genomic and associated omics data related to Alzheimer's Disease (AD), Alzheimer's Disease Related Dementias (ADRD), as well as healthy aging. Serving as the data coordinating center for the Alzheimer's Disease Sequencing Project (ADSP), NIAGADS hosts all ADSP-generated whole-exome, whole-genome and associated phenotypes. Other data types hosted by NIAGADS include genotype SNP arrays, functional omics, fluid biomarkers, aggregated imaging data (such as volumetric data for brain regions of interest), and summary statistics. In adherence with NIH security best practices and genome data sharing policies, NIAGADS supports data access requests through review by an NIH-appointed and registered Data Access Committee. Data stored within NIAGADS cannot be requested via dbGaP. Data requests must go through the NIAGADS Data Sharing Service (DSS) via the following NIAGADS url: https://dss.niagads.org/. Questions related to the request of data should be directed to the NIAGADS admin team at: niagads@pennmedicine.upenn.edu. DSS is a FISMA certified platform built by a team of data scientists at the University of Pennsylvania to support the request and access of AD/ADRD data by qualified researchers internationally. Questions related to the use of data hosted in the DSS should be directed to the Portal admin team at: help@niagads.org.

  Study phs004180

• Exome and RNA sequencing of relapsed TCF3-PBX1 t(1;19) acute lymphoblastic leukemia

  TCF3-PBX1 (E2A-PBX1) is a recurrent gene fusion in B-cell precursor lymphoblastic leukemia (BCP-ALL), which is caused by the translocation t(1;19)(q23;p13). TCF3-PBX1 BCP-ALL patients typically benefit from chemotherapy; however, many relapse and subsequently develop resistant disease with few effective treatment options. Mechanisms driving disease progression and therapy resistance have not been studied in TCF3-PBX1 BCP-ALL. Here, we aimed to identify novel treatment options for TCF3-PBX1 BCP-ALL by profiling leukemia cells from a relapsed patient, and determine molecular mechanisms underlying disease pathogenesis and progression. By drug sensitivity testing of leukemic blasts from the index patient, control samples and TCF3-PBX1 positive and negative BCP-ALL cell lines, we identified the phosphatidylinositide 3-kinase delta (p110δ) inhibitor idelalisib as an effective treatment for TCF3-PBX1 BCP-ALL. This was further supported by evidence showing TCF3-PBX1 directly regulates expression of PIK3CD, the gene encoding p110δ. Other somatic mutations to TP53 and MTOR, as well as aberrant expression of CXCR4, may influence additional drug sensitivities specific to the index patient and accompanied progression of the disease. Our results suggest that idelalisib is a promising treatment option for patients with TCF3-PBX1 BCP-ALL while other drugs could be useful depending on the genetic context of individual patients.

  Study EGAS00001001876

• Using_genetics_to_identify_cell_types_and_mechanisms_underlying_susceptibility_to_primary_sclerosing_cholangitis

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

  Study EGAS00001002643

• Using_genetics_to_identify_cell_types_and_mechanisms_underlying_susceptibility_to_primary_sclerosing_cholangitis

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

  Study EGAS00001002642

• Prime editing for functional repair in patient-derived disease models

  Prime editing is a novel genome editing technology using fusion proteins of Cas9-nickase and reverse transcriptase, that holds promise to correct a wide variety of genetic defects. We succeeded in efficient prime editing and functional recovery of disease-causing mutations in patient-derived liver and intestinal stem cell organoids. Whole genome sequencing of did not detect off-target mutations or a mutational signature induced by prime editing.

  Study EGAS00001004611

• Acquisition of additional mutations drives accelerated progression of NPM1 positive CMML to AML

  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/ We performed exome sequencing on serial samples from a patient with CMML who progressed to AML. The exome sequencing suggests that NPM1, TET2 and DNMT3a mutations were present in the dominant clone in the CMML sample and that NRAS is a new subclonal mutation in the AML sample. Diagnostic data shows the presence of a FLT3-ITD mutation in the AML sample, which is likely to have driven progression. Here we are performing re-sequencing of the putative driver and some passenger mutations which appear to be in the same clone to validate these mutations and to verify the relative quantification of these abnormalities .

  Dataset EGAD00001002194

• Pseudodiastrophic dysplasia expands the known phenotypic spectrum of defects in proteoglycan biosynthesis

  Pseudodiastrophic dysplasia (PDD) is a severe skeletal dysplasia associated with prenatal manifestation and early lethality. Clinically, PDD is classified as a ‘dysplasia with multiple joint dislocations’ however, the molecular aetiology of the disorder is currently unknown. In order to identify the genetic defects underlying PDD, we performed whole exome sequencing (WES) on 3 patients from 2 unrelated families, clinically diagnosed with PDD. WES resulted in the identification of bi-allelic variants in the established skeletal dysplasia genes, B3GAT3 (Family 1) and CANT1 (Family 2). Mutations in these genes have previously been reported to cause ‘multiple joint dislocations, short stature, and craniofacial dysmorphism with or without congenital heart defects’ (B3GAT3) and Desbuquois dysplasia 1 (CANT1); disorders in the same nosological group as PDD. Follow-up of the B3GAT3 variants demonstrated significantly reduced B3GAT3/GlcAT-I expression. Downstream in vitro functional analysis revealed abolished biosynthesis of glycosaminoglycan side chains on proteoglycans. Functional evaluation of the CANT1 variant showed impaired nucleotidase activity, which results in inhibition of glycosaminoglycan synthesis through accumulation of uridine diphosphate. For the families described in this study, the PDD phenotype was caused by mutations in the known skeletal dysplasia genes B3GAT3 and CANT1, demonstrating the advantage of genomic analyses in delineating the molecular diagnosis of skeletal dysplasias. This finding expands the phenotypic spectrum of B3GAT3- and CANT1- related skeletal dysplasias to include PDD, and highlights the significant phenotypic overlap of conditions within the proteoglycan biosynthesis pathway.

  Study EGAS00001004145

• The Genomic Landscape of Response to EGFR Blockade in Colorectal Cancer

  Colorectal cancer (CRC) is the third most common cancer world-wide with 1.2 million patients diagnosed yearly. In late stage CRC, the most commonly used targeted therapies are monoclonal antibodies cetuximab and panitumumab, which inactivate EGFR. Recent studies have identified alterations in KRAS and other genes as likely mechanisms of primary and secondary resistance to anti-EGFR antibody therapy. Despite these efforts, additional mechanisms of resistance to EGFR blockade are thought to be present in CRC and little is known about determinants of sensitivity to this therapy. To examine the effect of somatic genetic changes in CRC on response to anti-EGFR antibody therapy, we performed complete exome sequence and copy number analyses of 129 patient-derived tumorgrafts and targeted genomic analyses of 55 patient tumors, all of which were KRAS wild-type. We analyzed the response of tumors to anti-EGFR antibody blockade in tumorgraft models or in clinical settings. In addition to previously identified genes, we detected mutations in ERBB2, EGFR, FGFR1, PDGFRA, and MAP2K1 as potential mechanisms of primary resistance to this therapy. Novel alterations in the ectodomain of EGFR were identified in patients with acquired resistance to EGFR blockade. Amplifications and sequence changes in the tyrosine kinase receptor adaptor gene IRS2 were identified in tumors with increased sensitivity to anti-EGFR therapy. Therapeutic resistance to EGFR blockade could be overcome in tumorgraft models through combinatorial therapies targeting actionable genes. These analyses provide a systematic approach to evaluate response to targeted therapies in human cancer, highlight new mechanisms of responsiveness to anti-EGFR therapies, and provide new avenues for intervention in the management of CRC.

  Study EGAS00001001305

• Altered oligodendrocyte heterogeneity in Multiple sclerosis revealed by single nuclei RNA sequencing

  This study is currently hosted by the European Nucleotide Archive. To access the data contained within the Study please follow the link below: https://www.ebi.ac.uk/ena/browser/view/PRJEB39323 Oligodendrocyte (OL) pathology is increasingly implicated in neurodegenerative diseases, as they are involved in metabolic support of axons and functional cross-talk with other brain cells. Rodent OLs are heterogeneous, with developmental and biological differences, but the extent of heterogeneity in the normal human brain and its contribution to any changes to disease remains unknown. Here we performed single nuclei RNA-sequencing (snRNA-seq) from white matter (WM) areas of post mortem human brain both in control (Ctr) and multiple sclerosis (MS) patients. We identified several sub-clusters of oligodendroglia in the Ctr human WM, some similar to those in mouse, and defined new markers for these cell states. Strikingly, some of these sub-clusters were under-represented in MS tissue, while others were more prevalent than in controls. We found a lack of OL precursor cells (OPCs) and an OL subcluster in an intermediate stage of differentiation in MS lesions and in normal appearing white matter (NAWM), suggesting either depletion by the disease or by a regenerative response. The differences in mature OL sub-clusters indicate different functional states of OLs in MS tissue and, as this is similar in NAWM to lesions, that MS is a more diffuse brain disease than the focal demyelinating lesions suggest. We were also able to identify new putative markers of different MS lesion subtypes. Our findings of an altered heterogeneity of oligodendroglia in MS may have an important contribution to our understanding of disease progression and may alter therapeutic approaches to MS.

  Study EGAS00001003412

• Metadata Public API

  Metadata Rest Endpoints Common Aspects Functionality Identifiers Requests and Responses Request Response Querying Querying by Object Cross-Querying by Object Common Aspects Functionality The Metadata REST API allows EGA users to request metadata from the EGA. Using this api you will be able to obtain the publicly available information from EGA study, sample, experiment, run, analysis, policy, dac and dataset. The API also allows for objects to be cross-referenced in order to obtain for example all the datasets linked to a dac. Identifiers EGA objects can be identified by their unique accession. These are ID's displayed everywhere, shared among all EGA locations and specific for each data type (More information on the list below) EGA Accession ID EGA Object description EGAS EGA Study Accession ID EGAC EGA DAC Accession ID EGAP EGA Policy Accession ID EGAN EGA Sample Accession ID EGAR EGA Run Accession ID EGAX EGA Experiment ID EGAZ EGA Analysis Accession ID EGAD EGA Dataset Accession ID EGAB EGA Submission ID EGAF EGA File Unique Accession ID Server Request and Response Request All the endpoints implement these two HTTP methods, GET and HEAD. Moreover, there is an authentication layer that allows to disclose the private information about each object if the user runs the endpoint with their token and has permissions to the related dataset. HTTP Method Description GET Returns the objects and their public information (including private information if the user has permissions) HEAD Returns the count of objects to be returned Response API responses are diverse but they always return a status call. Below you have a summary on what these codes mean and some tips that can help you troubleshooting them: HTTP Status Code Description Resolution 200 OK No error handling necessary 206 Partial Content Expected status code when paginating the results. No error handling necessary 400 BAD REQUEST Request incorrectly formulated 401 UNAUTHORISED/FORBIDDEN You do not have permissions over the object you are trying to access. / The authorised user is not permitted to make the given request. 404 NOT FOUND The object/resource you are trying to access does not exist. 500 INTERNAL SERVER ERROR This is a server-side error, try later. If the issue persists, contact the Heldpesk. Querying Querying by Object In the below documentation, worked examples can be found on how to use the API, to query about each unique EGA object. https://metadata.ega-archive.org/analyses/{id} https://metadata.ega-archive.org/dacs/{id} https://metadata.ega-archive.org/datasets/{id} https://metadata.ega-archive.org/runs/{id} https://metadata.ega-archive.org/samples/{id} https://metadata.ega-archive.org/studies/{id} Worked example for the EGA data access committee(DAC) EGAC00001000514 https://metadata.ega-archive.org/dacs/EGAC00001000514 Points to notice Please, be advised that all EGA objects can be queried by using the same endpoint. For example: https://metadata.ega-archive.org/datasets Returns all the datasets registered at the EGA. https://metadata.ega-archive.org/datasets?limit=5&offset=15 Returns 5 results skipping the initial 15 results. Cross-Querying by Object The EGA REST API Metadata also allows for the crossquerying of public metadata. For example, should I want to query the datasets included in the ICGC DAC: https://metadata.ega-archive.org/dacs/EGAC00001000010/datasets Below, you can find worked examples on how to perform the call to the API. https://metadata.ega-archive.org/datasets/EGAD00001000645/analyses https://metadata.ega-archive.org/datasetsEGAD00001000645/files https://metadata.ega-archive.org/datasets/EGAD00001000620/runs https://metadata.ega-archive.org/datasets/EGAD00001000620/samples https://metadata.ega-archive.org/samples/EGAN00001092114/datasets https://metadata.ega-archive.org/files/EGAF00000056146/dacs https://metadata.ega-archive.org/files/EGAF00000056146/datasets https://metadata.ega-archive.org/files/EGAF00000056146/studies There are more endpoints included in this category. Please, find all the possibilities (green tick) in the table below. Table The table displays in a ordered fashion the objects that can be crossreferenced using the metadata API. BY Analysis Dac Dataset Experiment Policy Run Sample Study File Analysis ✔ ✔ Dac ✔ ✔ Dataset ✔ ✔ ✔ ✔ Experiment ✔ ✔ ✔ ✔ Policy ✔ Run ✔ ✔ ✔ Sample ✔ ✔* ✔ Study ✔ ✔ ✔ ✔ ✔ ✔* File ✔ *: These cross queries do not include data from Array-File submissions. Check out the SPEC

  Documentation discovery/metadata/public-metadata-api