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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

• Systems biology of Colorectal Cancer

  Colorectal cancer (CRC) is one of the most common cancers in both males and females, and it is perhaps the best understood of all epithelial tumors in terms of its molecular origin. Yet, despite large amount of work that has concentrated on understanding of colon tumorigenesis, we still do not know the full complement of molecular lesions that are individually necessary – and together sufficient – to cause colorectal cancer. Neither do we understand why some specific mutations that are relatively rare in other tumors (e.g. loss of the APC tumor suppressor) are extremely common in colorectal cancer. We propose here to use the tools of systems biology to develop a quantitative and comprehensive model of colorectal tumorigenesis. The model will include identification of cell-type specific and oncogenic pathways that contribute to colon tumorigenesis, and explain in molecular detail how a genotype of an individual CRC leads to activation of downstream genes that drive uncontrolled cell growth. This model will subsequently be used to find novel therapeutic targets, to guide genetic screening to identify individuals with elevated risk for developing CRC, and to classify patients into molecular subgroups to select the treatment combination that is optimal for each patient (personalized medicine). The specific objectives of the SYSCOL project are: 1. Identify genetic markers for individual risk using genotyping and sequencing of constitutional DNA from sporadic and familial CRC cases and controls 2. Identify genes and regulatory elements that contribute to colorectal cancer cell growth 3. Use data from Aims 1-2 to develop a quantitative model for colorectal tumorigenesis 4. Apply the model for identification of high-risk individuals, for molecular classification of the disease, and for identification of novel molecular treatment targets

  Study EGAS00001000854

• 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

• Exceptional Outcomes in a Phase Ib Study Combining PARP and MEK Inhibition, With or Without Anti-PD-L1, for BRCA-Wildtype Platinum-Sensitive Recurrent Ovarian Cancer

  To evaluate regimens combining PARP and MEK inhibition, with or without PD-L1 inhibition, for BRCA-wildtype platinum-sensitive recurrent ovarian cancer (PSROC).

  Study EGAS00001007496

• Processed Total RNA Counts for the RNA Profiling from Indian HFrEF Cohort Dataset

  This dataset contains processed RNA count data for the 49 Heart Failure samples profiled by RNAseq for the Indian HFrEF Cohort from the study Integrated Transcriptomic and Regulatory RNA Profiling Reflects Complex Pathophysiology and Uncovers a Conserved Gene Signature in End Stage Heart Failure RNA-Seq data.

  Dataset EGAD50000001193

• Processed miRNA Counts for the miRNA Profiling from Indian HFrEF Cohort Dataset

  This dataset contains processed miRNA count data for the 49 Heart Failure samples profiled by miRNAseq for the Indian HFrEF Cohort from the study Integrated Transcriptomic and Regulatory RNA Profiling Reflects Complex Pathophysiology and Uncovers a Conserved Gene Signature in End Stage Heart Failure RNA-Seq data.

  Dataset EGAD50000001195

• Sequencing data for Hepatoblastoma samples

  This dataset contains DNA sequencing data for twelve hepatoblastoma tumor samples, four of which have matched normals. Nine of the samples also have RNA sequencing data from the tumor sample. The dataset comprises six samples from patient tissues and six from cell lines; see metadata for details.

  Dataset EGAD00001006621

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

  Genomic determination for Homologous Recombination Deficiency (HRD) by shallow Whole Genome Sequencing (sWGS) with shallowHRD (PMID : 32315385) on 55 triple-negative breast cancer Patient Derived-Xenograft (PDX) treated with platinum.

  Study EGAS00001005926

• Learning from the thymic human cell atlas for T cell engineering: Paediatric RNA (2025-10-02)

  T cells are central to adaptive immunity and thus crucial for understanding and treating human disease. While extensively studied in model organisms, translating this knowledge to humans can sometimes be limited by their rapid cross-species evolution and diverse . This dataset contains all the data available for this study on 2026-03-10.

  Dataset EGAD00001015720

• PDAC Phenotype and Germline Genotype Data Access Committee

  This Data Access Committee (DAC) is responsible for reviewing and approving requests for access to controlled phenotype metadata and derived germline FUT2/FUT3 genotype data from patients with pancreatic ductal adenocarcinoma (PDAC). Access is granted to bona fide researchers for non-commercial research purposes only, subject to approval by the DAC and in accordance with the original informed consent and applicable ethical regulations.

  Dac EGAC50000000893

• Genome-wide genotype data for 1,433 ni-Vanuatu

  Here, we generated genome-wide genotype data for 1,433 contemporary ni-Vanuatu and assessed their fine-scale genetic structure, in order to address central questions about the settlement of western Remote Oceania.

  Study EGAS00001005910

• Identification_and_functional_validation_of_driver_mutations_in_colorectal_cancer

  Targeted exome sequencing of human colorectal cancers for the identification of novel cancer drivers.

  Study EGAS00001000044

• Carcinoma of the oral tongue (OTSCC) genomic landscape characterisation

  18 Exomes for discovery set and 60 Targeted panel for prevalence set

  Dataset EGAD00001001465

• Array data for oesophageal and related samples - aks_paper_methyl_barretts_release

  Array data for oesophageal and related samples - aks_paper_methyl_barretts_release

  Dataset EGAD00010001972

• Methylation files for Roussel-ATRT-TM

  Methylation files for Roussel-ATRT-TM paper titled "Atypical teratoid/ rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities"

  Dataset EGAD00010002357

• TOPARP-B patient cell-free DNA targeted sequencing

  Targeted sequencing for TOPARP-B patients as detailed in manuscript

  Study EGAS50000000281

• Yale Policy for head and neck cancer and HPV clinical trials

  Yale Policy for human controlled access data associated with head and neck cancer and HPV clinical trials

  Dac EGAC50000000403

• RNAseq for CIAO Clinical Trial

  RNAseq (QuantSeq) from FFPE tissues for the CIAO clinical trial

  Dataset EGAD50000001676

• PACA-CA Whole Genome Sequence bam files

  Merged bam files for PACA-CA Whole Genome Sequencing, for DCC release 27

  Dataset EGAD00001003927

• RNASeq files for GenomePaint paper

  RNASeq files for GenomePaint paper titled "Exploration of coding and non-coding variants in cancer using GenomePaint."

  Dataset EGAD00001006680

• DATA FILES FOR SJOS-WGS-2ndBatch

  DATA FILES FOR SJOS-WGS-2ndBatch

  Dataset EGAD00001001053

• WGS fastq for EGAS00001004572

  Bulk WGS fastq files for germline and tumours in EGAS00001004572.

  Dataset EGAD00001006902

• PACA-CA RNASeq bam files

  Bam files for PACA-CA RNA Seq analysis, for DCC release 27

  Dataset EGAD00001003945

• PACA-CA Whole Genome Sequence bam files

  Merged bam files for PACA-CA Whole Genome Sequencing, for DCC release 27

  Dataset EGAD00001003948