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• DAC for the Canadian Biobank on Respiratory and Allergic diseases (CoBRA)

  Dac EGAC00001000901

• DAC: Whole transcriptome RNA sequencing as comprehensive diagnostic tool for acute myeloid leukemia.

  Dac EGAC00001000956

• DAC for project: Subcutaneous panniculitis-like T-cell lymphomas (SPTCL) with hemophagocytic lymphohistiocytic syndrome.

  Dac EGAC00001000992

• FORTH-BRFAA DAC for Systemic Lupus Erythematosus (SLE)

  Dac EGAC00001001213

• RNA-seq from FFPE - Englander Institute for Precision Medicine - Weill Cornell Medicine DAC

  Dac EGAC00001002098

• Cancer Clinical Research Trust DAC for the 23 WES samples of melanoma subtypes

  Dac EGAC00001002402

• Coloured Project - Lankheet et al

  The data is for non-commercial use only.

  Dac EGAC50000000240

• The Data Access Committee for Human Olfactory Mucosa Cells (DAC HOM) at UEF

  Dac EGAC00001003404

• DAC for scRNA-seq and scp-MS data on human bone marrow

  Dac EGAC00001003505

• DAC_MATCH-R molecular driver

  Data access committee for MATCH-R molecular driver study

  Dac EGAC50000000335

• human HYPOMAP

  Data access for HYPOMAP raw sequence data and result data objects

  Dac EGAC50000000410

• This DAC will review all requests for data related to the dataset: EGAD00001015613.

  Dac EGAC00001003562

• DAC for DNA methylation data (iMED, BCG prime, and 500FG)

  Dac EGAC00001003534

• human biopsies

  DAC for human samples derived from biopsies from patients with hydrocephaly.

  Dac EGAC50000000625

• CoV2 challenge data

  Repository containing the transcriptomic data for the CoV2 challenge study

  Dac EGAC50000000391

• H3N2 challenge data

  Repository containing the transcriptomic data for the H3N3 challenge study

  Dac EGAC50000000379

• A machine learning classifier for DNA repair defects using plasma DNA

  Study EGAS00001007006

• CITE-seq for peripheral blood samples of 5 breast cancer patients

  Study EGAS00001006241

• Initial cohort of 500 solid tumors screened for Basket of Baskets

  Study EGAS00001005893

• Tapestri_h5

  H5 files generated for each sample with Tapestri Pipeline

  Dataset EGAD00010002559

• Tapestri_loom

  Loom files generated for each sample with Tapestri Pipeline

  Dataset EGAD00010002561

• GermlineSNP

  SNP data for 473 germline samples

  Dataset EGAD00010002039

• PopArg94_raw

  Raw data files for 94 Argentinean samples

  Dataset EGAD00010001913

• Validation of cfDNA fragmentome analyses for early detection of liver cancer

  Study EGAS00001008111

• Neutrophils as effector cells in resistance to infection by Mtb

  Dac EGAC00001003255

• Latency and interval therapy affect the evolution in metastatic colorectal cancer.

  Dac EGAC00001001198

• The mutational landscape of skin tumours in CYLD cutaneous syndrome

  Dac EGAC00001001305

• TCR sequencing of TIL in breast cancer data access committee

  Dac EGAC00001003173

• Mechanisms of duodenal adenoma development in familial polyposis syndromes

  Study EGAS00001006561

• Mesenchymal niche in myelodysplastic hematopoiesis at single cell resolution

  Study EGAS00001007568

• NK cells in chronic viral hepatitis Data Access Committee

  Dac EGAC50000000530

• MD Anderson Data Access Committee: Pembrolizumab in Advanced Rare Cancers

  Dac EGAC50000000860

• Resident memory CD8 T cell in human lung cancer

  Study EGAS00001004707

• Frequencies of variants in the Danish population

  Study EGAS00001006786

• APOBEC mutagenesis in EGFR mutant TKI resistance NSCLCs

  Study EGAS00001005526

• Exome sequencing in CLL re-treated with venetoclax

  Study EGAS00001006158

• RMS_Infinium450K

  Infinium 450K in Rhabdomyosarcoma

  Dataset EGAD00010000897

• Rapid Acceleration of Diagnostics - Digital Health Technologies (RADx-DHT): NIH Digital Health Solutions for COVID-19: SAFER-COVID - Integration of Testing and Digital Health

  SAFER-COVID provides a set of self-management tools to consumers to track symptoms, test results, vaccine record, and environmental factors, such as exposure to others. Consumers may choose to integrate data from wearables and electronic health records (EHR) for self management. These data are used to enable multiple use cases such as return-to-work, activity risk assessment and self-management within SAFER-COVID.DOI: https://rapids.ll.mit.edu/10.57895/cmt5-gh78

  Study phs002540

• Tools

  EGA Tools This page provides details of the applications available at the EGA. Submission Tool Description EgaCryptor Encrypt and create md5sum values. Crypt4gh Encrypt, decrypt or re-encrypt files. INBOX Upload your files once encrypted. FTP Upload your files once encrypted. Submitter Portal Submit and manage your submission metadata online (SEQUENCING AND PHENOTYPE ONLY) Submitter Portal API Submit and manage your submission metadata programmatically. Webin Submit and manage your submission metadata online (array data) Webin API Submit metadata using XML files. Aimed to array-based submissions. Star2xml Format conversion tool to transform tabular formats (e.g. spreadsheets) into EGA's XMLs. Used for large programmatic submissions. Data Access Tool Description DAC Portal Manage and control data access request. Download Tool Description PyEGA3 Download and decrypt datasets requested through your EGA web account. Live Outbox Download and decrypt datasets requested through your EGA web account. Fuse Client A quick and convenient way to browse through EGA files without the need for complete downloads. EGA QuickView A quick and convenient way to browse through EGA files without the need for complete downloads.

  Documentation tools

• Whole-genome sequences of single-cell derived clonal samples and bulk blood samples from human

  Human single cells were clonally expanded by culture and whole-genome sequenced. This dataset includes 334 clonal samples and 7 blood bulks from seven individuals (DB2, DB3, DB5, DB6, DB8, DB9, DB10). We extracted genomic DNA materials from clonally expanded cells and matched peripheral blood using DNeasy Blood and Tissue kits (Qiagen) according to the protocol. DNA libraries for WGS were generated by an Accel-NGS 2S Plus DNA Library Kit (Swift Biosciences) from 1 µg of genomic DNA materials. WGS was performed on either the Illumina HiSeq X platform or the NovaSeq 6000 platform to generate mean coverage of 25.2X for 374 clonally expanded cells and 94.8X for 7 matched blood tissues.

  Dataset EGAD00001007032

• CCA ChIP-seq data (63 CCA, 8 normal, 19 cell-line)

  Fastq files for H3K27ac ChIP-seq (with matched input-DNA control) for 63 CCAs, 8 normal bile duct tissues, 16 CCA cell-lines (including replicates), and 3 normal cholangiocyte cell-lines (including replicates). Library prep was performed with the NEBNext ChIP-seq library preparation kit. Each library (including matching input DNA) was sequenced to an average depth of 20 to 30 million raw reads on Illumina HiSeq4000 sequencer, with paired-end sequencing (except for 3 normal bile tissues done with single-end sequencing).

  Dataset EGAD00001012103

• NHLBI GO-ESP: Family Studies (Familial Interstitial Pneumonia)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The Familial Interstitial Pneumonia (FIP) project seeks to identify genetic variants in coding regions of the human genome that are linked to FIP by examining the coding regions among relatives with FIP. These data will be used in conjunction with our other genetic studies to help us better understand how and why some individuals develop pulmonary fibrosis.

  Study phs000582

• Systems Analysis of Single-Cell Heterogeneity Underlying Glioma Drug Resistance

  This study characterizes the transcriptional regulatory mechanisms that drive responses of two patient-derived glioblastoma multiforme (GBM) stem-like cells (PD-GSCs) that have distinct phenotypes - one sensitive and another resistant to the drug pitavastatin. This study investigates the differing mechanisms driving drug response in the two PD-GSCs at the single-cell level, and provides an approach that can be used to infer transcriptional regulatory network models, which can then be used to identify mechanisms driving cell-state transitions, e.g., proneural-to-mesenchymal transitions (PMT), which has been observed experimentally and clinically in GBM. The use of these network models enabled the identification of transcription factor and gene targets that perturbed drug-induced PMT through 1) simulations of network dynamics network, and 2) characterization of gene program activities over the time-course response to drug treatment. These results enabled the identification of multiple siRNAs and the drug vinflunine as secondary components that potentiate the efficacy of pitavastatin. This work demonstrates an approach to uncover the transcriptional network topology (TRN) topology of PD-GSCs, and use it to rationally predict combinatorial treatments that block treatment escape and acquired resistance to drugs in GBM.

  Study phs003501

• Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types

  The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1,070 tumor and 493 normal samples in combination with pan-cancer 137 spatial transcriptomics, 8,887 TCGA, and 1,261 checkpoint inhibitor-treated bulk tumors. We define a myriad of cell states constituting the tumor-normal ecosystems and also identify hallmark gene signatures across different cell types and organs. Our atlas characterizes distinctions between inflammatory fibroblasts marked by AKR1C1 or WNT5A in terms of cellular interactions and spatial co-localization patterns. Co-occurrence analysis reveals interferon-enriched community states including tertiary lymphoid structure (TLS) components, which exhibit differential rewiring between tumor, adjacent normal, and healthy normal tissues. The favorable response of interferon-enriched community states to immunotherapy is validated using immunotherapy-treated cancers (n=1,261) including our lung cancer cohort (n=497). Deconvolution of spatial transcriptomes discriminates TLS-enriched from non-enriched cell types among immunotherapy-favorable components. Our systematic dissection of tumor-normal ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity.

  Study EGAS50000000324

• Clonal evolution in myeloma: the impact of maintenance lenalidomide and depth of response on the genetics and sub-clonal structure of relapsed disease in uniformly treated newly diagnosed patients

  The emergence of treatment resistant sub-clones is a key feature of relapse in multiple myeloma. Therapeutic attempts to extend remission and prevent relapse include the maximisation of response and use of maintenance therapy. We used whole exome sequencing to study the genetics of paired presentation and relapse samples from 56 newly diagnosed patients, following induction therapy, randomised to receive either lenalidomide maintenance or observation as part of the Myeloma XI trial. Patients included were considered high risk, relapsing within 30 months of maintenance randomisation. Patients achieving a complete response had predominantly branching evolutionary patterns leading to relapse, characterised by a greater mutational burden, an altered mutational profile, bi-allelic inactivation of tumour suppressor genes, and acquired structural aberrations. Conversely, in patients achieving a partial response the evolutionary features were predominantly stable with a similar mutational and structural profile. There were no significant differences between patients relapsing after maintenance lenalidomide vs observation. This study shows that the depth of response is a key determinant of the evolutionary patterns seen at relapse.

  Study EGAS00001003539

• Whole genome sequence and RNA-seq data from paired tumour and germline samples from mesothelioma patients.

  Malignant pleural mesothelioma (MPM) has a poor overall survival with few treatment options. Whole genome sequencing (WGS) combined with RNA sequencing (RNA-seq) analysis of the immune features of MPM offers the prospect of identifying changes that could inform future clinical trials. We analysed somatic mutation and RNA-seq data from 229 MPM samples, including 58 MPM samples that had undergone WGS from our own institutions, together with other published data. This combined analysis identified somatic driver genes, including newly identified candidate genes. Whole genome doubling was a frequent event that correlated with shorter survival. Mutational signature analysis revealed dominant signatures and showed that defects in homologous recombination repair were infrequent in our cohort. Within the tumour immune environment we identified high M2 macrophage infiltrate linked with MMP2, MMP14, TGFB1 and CCL2 expression, representing an immunosuppressive environment. A small subset of samples had a higher proportion of CD8 T cells and a high cytolytic score, suggesting a ‘hot’ immune environment which is independent of the somatic mutations. We propose that our findings on genomic changes and subtypes of immune microenvironments may influence therapeutic planning in the future.

  Study EGAS00001005196

• Molecular_risk_stratification_in_patients_with_T1_colorectal_cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have ‘born-to-be-bad’ aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world’s largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3’ RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Study EGAS00001005734

• Cancer Genetic Markers of Susceptibility (CGEMS) Breast Cancer Genome-wide Association Study (GWAS) - Primary Scan: Nurses' Health Study - Additional Cases: Nurses' Health Study 2

  The initial stage of the Cancer Genetic Markers of Susceptibility (CGEMS) breast cancer genome-wide association study (GWAS) included genotyping 528,173 SNPs (Illumina HumanHap550) in 1,145 postmenopausal women of European ancestry with invasive breast cancer and 1,142 controls from the Nurses' Health Study (NHS). Subsequently, incident invasive breast cancer cases from the Nurses' Health Study 2 (NHS2) cohort were genotyped using the Illumina HumanHap 610 quad. The NHS2 cases are younger than the cases in the first stage of the CGEMS breast cancer GWAS, which only included postmenopausal women. The NHS2 cases are a mix of pre- and postmenopausal women

  Study phs000147

• Ameloblastoma Cell Line Resource

  Ameloblastoma (AB) is an odontogenic tumor that is locally destructive to the jaw bone. Treatment entails surgical resection, but AB often recurs locally. Recent driver mutations have been identified in the MAPK and Hedgehog pathways. However, translation to molecularly-targeted therapies has been hampered by the lack of AB cell line models. The goal of our study has been to create a new AB cell line resource that reflects the spectrum of AB driver mutations. We created 6 new AB cell lines, and by targeted exome sequencing, defined their driver mutations. We showed the utility of these cell lines in preclinical studies of oncogene dependence and drug sensitivity (which includes whole transcriptome assays).

  Study phs002753

• National Institute of Mental Health (NIMH) Amish Mennonite Bipolar Genetics Study (AmBiGen)

  Bipolar affective disorder is a severe, heritable condition affecting about one percent of the population. The mode of inheritance is poorly understood and probably involves multiple loci of small to moderate effect. In this project, we use genetic mapping and sequencing methods to identify genetic markers and variations that contribute to the risk of bipolar disorder. Individuals diagnosed with bipolar disorder are studied, along with their relatives. Phenotypic information obtained from clinical interviews and family history is correlated with genotypic information obtained from genetic marker and sequencing methods. The goal is to identify genes involved in bipolar disorder and related conditions so that better methods of diagnosis, treatment, and prevention can be developed.

  Study phs000899