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• HCA_Gut_Paediatric_Hirschsprung_s_disease_Teichmann_RNA_Managed_Access_

  This study involves atlasing the development of the postnatal gut nervous system in order to elucidate the pathogenic mechanisms of Hirschsprung disease.

  Study EGAS00001007151

• Kuusamo whole exome sequencing

  Whole exome sequencing of samples selected from the Finrisk sample collection. The samples sequenced in this study have all been collected in Kuusamo, Finland.

  Dataset EGAD00001000299

• WES melanoma biopsies (UV1-hTERT-mm)

  The dataset contains phenotypes of 14 melanoma biopsies sequenced in connection with the study UV1-hTERT-mm, where the thereapeutic cancer vaccine UV1 is combined with ipilimumab in treatment of melanoma patients.

  Dataset EGAD00001007648

• Gain of Function Mutations in RPA1

  Exome sequencing and amplicon-based single-cell sequencing dataset on the patients and family members that were analyzed in this study.

  Dataset EGAD00001008329

• Genomics of drug sensitivity in acute lymphoblastic leukemia

  Genomics of drug sensitivity in acute lymphoblastic leukemia

  Dataset EGAD00001009000

• Germline WES data of children with pathogenic mutations in cancer predisposing genes

  This data set includes bam files (aligned to hg38) from the germline of children who have pathogenic mutations in cancer predisposing genes

  Dataset EGAD00001009854

• The Library of Integrated Network-Based Cellular Signatures (LINCS) - NeuroLINCS

  The NeuroLINCS Center is part of the NIH Common Fund's Library of Integrated Network-based Cellular Signatures (LINCS) program, which aims to characterize how a variety of human cells, tissues and the entire organism respond to perturbations by drugs and other molecular factors. As Part of the LINCS program, the NeuroLINCS study concentrates on human brain cells, which are far less understood than other cells in the body. Our initial focus is to produce diseased motor neurons from patients by utilizing high-quality induced pluripotent stem cell (iPSC) lines from Amyotrophic Lateral Sclerosis (ALS) and Spinal Muscular Atrophy (SMA) patients in addition to unaffected normal healthy controls. Using state-of-the-art OMICS methods (genomics, epigenomics, transcriptomics, and proteomics), we intend to create a wealth of cellular data that is patient-specific in the context of their baseline genetic perturbations and in the presence of other genetic and environmental perturbagens (e.g. endoplasmic reticulum stress). The primary data will be used to build cell signatures that convey the key features that distinguish the state of a cell and determine its behavior. Ultimately, the analysis of these datasets will lead to the identification of a network of unique signatures relevant to each of these motor neuron diseases. The datasets represented in this study are generated from assays interrogating RNA expression (RNA-seq), chromatin accessibility (ATAC-seq) and whole genome sequencing.

  Study phs001231

• University of Washington Center for Mendelian Genomics (UW-CMG): Atrioventricular Septal Defects (AVSD) Study

  The Centers for Mendelian Genomics project uses next-generation sequencing and computational approaches to discover the genes and variants that underlie Mendelian conditions. By discovering genes that cause Mendelian conditions, we will expand our understanding of their biology to facilitate diagnosis and new treatments.

  Study phs001774

• comprehensive genetic analysis and database construction for head and neck cancer

  The main purpose is to conduct comprehensive genetic analysis of head and neck malignant tumor tissue and patient-derived blood, and to construct a database for it. By analyzing these databases, we aim to clinically identify recurrence and metastasis prediction markers and establish new molecular target therapies.

  Study JGAS000214

• TTFields Glioblastoma Data Access Committee, Charité – Universitätsmedizin Berlin

  This Data Access Committee is responsible for reviewing and approving data access requests for genomic and associated clinical data from patients with glioblastoma, IDH wildtype, treated with surgery, standard chemoradiotherapy and Tumor Treating Fields at Charité – Universitätsmedizin Berlin. The DAC ensures that any data use is consistent with the patients’ informed consent, the study’s ethical approval and applicable data protection regulations. Approved applicants may use the data only for biomedical research on brain tumours and related methods, must not attempt re-identification of participants, and may not share the data with unauthorized third parties

  Dac EGAC50000000843

• CEITEC DAC

  A CEITEC Data Access Committee (DAC) is a body of one or more named individuals who are responsible for data release to external requesters. The members of DAC are selected members of research groups and their respective leaders. Multiple datasets may be affiliated to a single DAC. DAC continues communication with requester to understand the purpose of use, i.e. research setting the dataset is envisioned for by requester, to identify if data sharing is possible directly under current conditions for the dataset, or actions such as re-consenting is needed and desirable to accommodate the proposed research setting/data use.

  Dac EGAC50000000049

• Clinical Outcomes for 344 Diffuse Large B-Cell Lymphoma Patients

  This dataset contains clinical outcomes for 344 Diffuse Large B-Cell Lymphoma patients. For each subject we have recorded AGE (binarized: > 60, <= 60), SEX (male or female), LDH (serum lactate dehydrogenase), ECOG (Performance status 3 or 4), STAGE (Disease stage III or IV according to the Ann Arbor staging system), EXBM (Two or more extranodal sites of disease (outside of a lymph node), BSYMP (Presence of B symptoms), and BM (Bone marrow involvement). All data are delivered as a single XLSX file with one row per patient.

  Dataset EGAD50000001536

• BLUEPRINT September 2016, ChIP-Seq for conventional dendritic cell from cord blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for conventional dendritic cell from cord blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002948

• BLUEPRINT September 2016, ChIP-Seq for memory B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) for memory B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002950

• BLUEPRINT September 2016, ChIP-Seq Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38

  ChIP-Seq data for 1 sample(s) Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_chipseq_analysis_ebi_20140811

  Dataset EGAD00001002949

• BLUEPRINT September 2016, RNA-Seq Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38

  RNA-Seq data for 6 sample(s) Acute Lymphocytic Leukemia for precursor B cell from venous blood, on Genome GRCh38. 6 run(s), 6 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002963

• BLUEPRINT September 2016, RNA-Seq Acute Myeloid Leukemia for blast cell from bone marrow, on Genome GRCh38

  RNA-Seq data for 1 sample(s) Acute Myeloid Leukemia for blast cell from bone marrow, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002962

• BLUEPRINT September 2016, RNA-Seq for monocyte T=10day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=10day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002961

• BLUEPRINT September 2016, RNA-Seq for monocyte T=6day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=6day_S100A9_RANKL_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002960

• BLUEPRINT September 2016, RNA-Seq for monocyte T=1day_M-CSF_S100A9_4hr_RANL from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=1day_M-CSF_S100A9_4hr_RANL from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002959

• BLUEPRINT September 2016, RNA-Seq for monocyte T=2day_RANK_M-CSF from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=2day_RANK_M-CSF from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002957

• BLUEPRINT September 2016, RNA-Seq T-cell lymphoma for helper T cell from venous blood, on Genome GRCh38

  RNA-Seq data for 2 sample(s) T-cell lymphoma for helper T cell from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002956

• BLUEPRINT September 2016, RNA-Seq for monocyte T=0day from venous blood, on Genome GRCh38

  RNA-Seq data for 1 sample(s) for monocyte T=0day from venous blood, on Genome GRCh38. 1 run(s), 1 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002955

• BLUEPRINT September 2016, RNA-Seq Acute Lymphocytic Leukemia for precursor B cell from bone marrow, on Genome GRCh38

  RNA-Seq data for 8 sample(s) Acute Lymphocytic Leukemia for precursor B cell from bone marrow, on Genome GRCh38. 8 run(s), 8 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002953

• BLUEPRINT September 2016, RNA-Seq Acute Myeloid Leukemia for myeloid cell from venous blood, on Genome GRCh38

  RNA-Seq data for 2 sample(s) Acute Myeloid Leukemia for myeloid cell from venous blood, on Genome GRCh38. 2 run(s), 2 experiment(s), 0 alignment(s). Part of BLUEPRINT (September 2016).Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001002968