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• Genetic Neuroscience: How Human Genes and Alleles Shape Neuronal Phenotypes

  The goal of this collaborative, interdisciplinary project is to develop powerful, generalizable approaches for discovering how risk variants for psychiatric disorders shape neurobiological processes at multiple levels of analysis, and to identify the processes whose dysregulation underlies disease.Induced pluripotent stem cells (iPSCs) were used towards the development of these new experimental and inferential systems bridging gaps between human genetics and experimental biology. The largest publicly available collection of iPSCs (2607 lines) has been generated from 2184 donors by the California Institute for Regenerative Medicine (CIRM). To expand our donor collection, an additional 44 iPSC donors from the McLean_Levy cohort were identified. We wish to share the available SNP data for 2167 CIRM lines and whole genome sequence data generated at the Broad Institute for 473 of the CIRM and 44 McLean_Levy iPSC donors. These data can be used to identify (for experiments) lines with specific genotypes of interest and lines from donors with high or low polygenic risk scores for phenotypes of interest. The data can also be used to identify acquired mutations in the iPSC lines. The CIRM iPSC lines are available through Fujifilm Cellular Dynamics iPSC Repository (https://www.fujifilmcdi.com/cirm-ipsc-products/). The McLean_Levy lines are available through the NIMH Repository & Genomics Resource (https://www.nimhgenetics.org/).Additional project data registered with the study includes data from an iPSC line derived from an SMA patient (n=1), as well as single-cell RNA sequence data and supplemental processed genomic datasets in support of project publications.Molecular DatasetsSingle-cell RNA-seq: 10X Genomics, Illumina NovaSeqSupplemental "cell village" pooled genomic sequence data: Illumina NextSeqWhole Genome Genotyping: Infinium Global Screening Array-24 Kit, Illumina HumanCore chipWhole Genome Sequencing: Illumina NovaSeq

  Study phs002032

• HeLa Cell Genome Sequencing Studies

  HeLa is a human epithelial adenocarcinoma cell line that was derived from biopsy specimens of a 31-year old patient named Henrietta Lacks who was being treated for cervical cancer at The Johns Hopkins University Hospital in 1951. The specimens were obtained without her knowledge or consent just before her death in 1951. HeLa is the oldest and most widely used human cell line and has been an extraordinarily important resource for researchers throughout the world. HeLa cells have served as a standard for understanding many fundamental biological processes, such as testing the polio vaccine, establishing basic techniques for cloning and in vitro fertilization, identifying the cause of cervical cancer (HPV), and advancing the development of anti-cancer drugs.This study contains all authorized whole genome sequence data of the HeLa cell line from datasets currently in dbGaP. These data have been approved for health, medical, and/or biomedical research purposes. Access to these data can be granted for one year. Accessible data will include the studies listed on this page and any additional authorized datasets that become available during this one-year period. The HeLa Genome Data Access Working Group of the Advisory Committee to the Director (ACD) will review requests from the research community for access to these datasets and assess whether the requests align with the terms of use defined in the HeLa Genome Data Use Agreement. The Working Group's findings will be reported to the ACD, and the ACD will make recommendations to the NIH Director about whether a request should be approved or disapproved. The NIH Director will decide whether access to the data will be granted.

  Study phs000640

• Whole exome sequencing of small cell neuroendocrine cancer of the cervix

  In order to improve treatment selection for high grade neuroendocrine carcinomas of the cervix (NECC), we performed a comparative genomic analysis between this rare tumor type and other cervical cancer types, as well as extra-cervical neuroendocrine small cell carcinomas of the lung and bladder. We performed whole exome sequencing on fresh-frozen tissue from 15 NECCs and matched normal tissue. We then identified mutations and copy number variants using standard analysis pipelines. Published mutation tables from cervical cancers and extra-cervical small cell carcinomas were used for comparative analysis. Descriptive statistical methods were used and a two-sided threshold of P < .05 was used for significance. In the NECC cohort, we detected a median of 1.7 somatic mutations per megabase (range 1.0-20.9). PIK3CA p.E545K mutations were the most frequency observed oncogenic mutation (4/15 tumors, 27%). Activating MAPK pathway mutations in KRAS (p.G12D) and GNAS (p.R201C) co-occurred in two tumors (13%). In total we identified PI3-kinase or MAPK pathway activating mutations in 67% of NECC. When compared to NECC, lung and bladder small cell carcinomas exhibited a statistically significant higher rate of coding mutations (P < .001 for lung; P = .001 for bladder). Mutation of TP53 was uncommon in NECC (13%) and was more frequent in both lung (103 of 110 tumors [94%], P < .001) and bladder (18 of 19 tumors [95%], P < .001) small cell carcinoma. These comparative genomics data suggest that NECC may be genetically more similar to common cervical cancer subtypes than to extra-cervical small cell neuroendocrine carcinomas of the lung and bladder. These results may have implications for the selection of cytotoxic and targeted therapy regimens for this rare disease.

  Study EGAS00001003142

• Data Access Committee for the DNA sequencing data included in the study "A generalizable machine learning framework for classifying DNA repair defects using ctDNA exomes”

  Dac EGAC00001003111

• PBMC

  Whole-Exome-Sequencing of 5 pooled patients for SNP-based demultiplexing

  Study EGAS50000000654

• SNP Array Data for EGAS00001004666

  SNP Array Data for EGAS00001004666

  Dataset EGAD00010002257

• DATA FILES FOR SJAMLM7

  DATA FILES FOR SJAMLM7

  Dataset EGAD00001000259

• "Usage of small amounts of DNA for Illumina sequencing"

  "Usage of small amounts of DNA for Illumina sequencing"

  Dataset EGAD00001000034

• WGS and WXS files for Dyer ATRX study

  WGS and WXS files for Dyer ATRX study

  Dataset EGAD00001003389

• DATA FILES FOR Histone Capture bams

  DATA FILES FOR Histone Capture bams

  Dataset EGAD00001000657