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• Whole genome sequencing raw data for fragile X associated unmethylated expansion carrier 2

  Whole genome sequencing raw data for fragile X associated unmethylated expansion carrier 2. DNA was sequenced using the illumina NovaSeq6000 system. 8x paired end FASTQ files from one DNA sample (UFM 2), 4x R1 files and 4x R2 files.

  Dataset EGAD50000000921

• CITE-seq data of six CK-AML patient samples

  We performed cellular indexing of transcriptomes and epitopes (CITE-seq) of six primary leukemia samples from CK-AML patients. The dataset contains BAM files for each individual sample (D1922 and R0836) or for the hashed pool (HIAML47-HIAML85, P9D-P9R)

  Dataset EGAD50000000633

• Dataset for early breast cancer samples

  This dataset contains WGS data for 27 tumor, control and patient derived culture samples of patients with breast cancer. Sequencing was performed on Illumina NovaSeq 6000 and HiSeq X using TruSeq Nano DNA Kit. The sequencing was always paired

  Dataset EGAD50000000860

• RNA-seq data for genomic determinants of response and resistance to inotuzumab in B-ALL

  RNA-seq data for 101 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000095

• WGS data for genomic determinants of response and resistance to inotuzumab in B-ALL

  Whole genome sequencing data for 45 samples with B-cell acute lymphoblastic leukemia

  Dataset EGAD50000000096

• Single cell and spatial transcriptomics of adult human adrenal glands

  The data set is composed of single cell transcriptomics data for adrenal glands from 11 deceased organ donors (10x 3') and spatial transcriptomic data for adrenal glands from 4 deceased organ donors (10x Visium).

  Dataset EGAD50000000394

• RNA-seq dataset for gamma delta (γδ) T-ALL patients

  RNA-seq data for 85 patients with acute lymphoblastic leukemia expressing the gamma delta T cell receptor (γδ T-ALL)

  Dataset EGAD50000000027

• Analysis_of_somatic_mutations_in_normal_blood__AML_and_MDS_samples

  Targeted pulldown of genes known to be recurrently mutated in AML & MDS from patient and normal samples using Agilent Sureselect and for some cases also using Illumina Truseq technology.

  Study EGAS00001000525

• Prognostic_factors_in_prostate_cancer__deep_sequencing_pilot_project_TAPG

  This is a pilot project to determine whether the TAPG FFPE DNA’s are suitable for deep sequencing. If successful an investigation of SNP distribution in a larger cohort will follow.

  Study EGAS00001000879

• Organoid_Derivation_Project___GRCh38___RNAseq

  Generation of normal and cancer organoids for sequencing as part of the WTSI-CRUK international collaboration with NCI (in HCMI) to generate the next generation of cancer cell lines.

  Study EGAS00001004677

• Organoid_Derivation_Project___GRCh38___WGS

  Generation of normal and cancer organoids for sequencing as part of the WTSI-CRUK international collaboration with NCI (in HCMI) to generate the next generation of cancer cell lines

  Study EGAS00001004712

• Bulk and single-cell AML RNA-seq post ex vivo culture

  Bulk and single-cell RNA-seq performed on primary AML blasts cultured ex vivo for 3 days in standard or niche-like conditions.

  Study EGAS00001006265

• Organoid_Derivation_Project___GRCh38___TGS

  Generation of normal and cancer organoids for sequencing as part of the WTSI-CRUK international collaboration with NCI (in HCMI) to generate the next generation of cancer cell lines.

  Study EGAS00001007349

• Genotyping of GM samples

  This dataset contains a vcf file for 99 GM individuals genotyped on the Illumina HumanOmni2.5 array . The vcf file is originated after imputation (IMPUTE2) and filtering for minor allele frequency MAF≥0.05, imputation confidence score INFO of >0.4 and Hardy-Weinberg Equilibrium (HWE) p>1e-06, yielding ~6.3 million variants.

  Dataset EGAD00001010255

• 16S bacterial amplicon sequencing data for Guangzhou cohort

  16S bacterial amplicon sequencing data for Guangzhou cohort

  Dataset EGAD00001010268

• WGS of NPC268_Tumor and NPC268_Cell_line

  This dataset contains WGS data in the form of BAM files for NPC268 - "Tumor" derived from snap-frozen tissue while "Cell line" derived from late passage NPC268 cell line. Extracted DNA was sent for 100x and 60x WGS with Novogene via Apical Scientific Sdn Bhd.

  Dataset EGAD00001010292

• Oncoprint GSCCs

  This dataset contains DNA sequencing data from 7 GSCCs (data for BT569 is not available). We performed focused exome sequencing (43 most mutated genes in GBM), combined with OneSeq analysis (Agilent) on the GSCCs and identified both shared and GSCC-specific mutations. For CME038, whole genome sequencing was performed.

  Dataset EGAD00001011276

• WGS files for paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  WGS files for Klco paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  Dataset EGAD00001015490

• WXS files for paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  WXS files for Klco paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  Dataset EGAD00001015491

• RNASeq files for paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  RNASeq files for Klco paper titled "Genomic Landscape and Clonal Architecture in Pediatric Myeloid Neoplasms with Chromosome 7 Deletions"

  Dataset EGAD00001015492

• High-throughput sequencing data for prostate methylome analysis

  Paired-end 150 (PE150) high-throughput sequencing data from 19 PCA, 29 BPH, and 19 BCA tissue samples. MeDIP-seq was employed to specifically enrich methylated DNA fragments across the genome, followed by methylation amplicon sequencing for further validation.

  Dataset EGAD50000002747

• GenomeDenmark Phase 2 - variants called on chrY for 62 males.

  Variants on the Y chromosome for 62 danish males in VCF format from the GenomeDenmark Phase 2 cohort. Variants were called using reference based approaches such as the haplotype-caller module from GATK and using alignment of denovo assemblies to the reference using ASMvar.

  Dataset EGAD00001003186

• V4 panel bait design test (2018-03-07)

  Targeted gene screen of FFPEs, cell lines and primary CRC tumours for testing the new V4 Colorectal gene panel. . This dataset contains all the data available for this study on 2018-03-07.

  Dataset EGAD00001004001

• BLUEPRINT release August 2015, DNase-Hypersensitivity for monocyte, on genome GRCh38

  DNase-Hypersensitivity data for 2 monocyte sample(s). 4 run(s), 2 experiment(s), 2 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_dnaseseq_analysis_20150820

  Dataset EGAD00001001560

• BLUEPRINT release January 2015, RNA-Seq for monocyte

  RNA-Seq data for 8 monocyte sample(s). 8 run(s), 8 experiment(s), 8 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_rnaseq_analysis_crg_20140811

  Dataset EGAD00001001191

• BLUEPRINT release January 2015, DNase-Hypersensitivity for macrophage

  DNase-Hypersensitivity data for 14 macrophage sample(s). 18 run(s), 14 experiment(s), 14 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

  Dataset EGAD00001001198

• DATA FILES FOR Ph-likeALL WES

  DATA FILES FOR Ph-likeALL WES

  Dataset EGAD00001001054

• BLUEPRINT release August 2014, DNase-Hypersensitivity for macrophage

  DNase-Hypersensitivity data for 1 macrophage sample(s). 1 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_dnaseseq_analysis_20140811

  Dataset EGAD00001000931

• WGS data for ependymomas (5 tumor-control pairs)

  Whole genome sequencing data for ependymomas (5 tumor-control pairs). See Mack, Witt et al. Nature 506(7489):445-50, 2014 (PMID: 24553142).

  Dataset EGAD00001000950

• WES/WXS data for ependymomas (42 tumor-control pairs)

  Whole exome sequencing data for ependymomas (42 tumor-control pairs). See Mack, Witt et al. Nature 506(7489):445-50, 2014 (PMID: 24553142).

  Dataset EGAD00001000951

• Carcinoid study - WGS dataset

  Fernandez-Cuesta et al., 2014, Nature Communication, Whole genome sequencing was performed using a read length of 2x100 bp for all samples. On average, 110 Gb of sequence were produced per sample, aiming a mean coverage of 30x for both tumour and matched normal.

  Dataset EGAD00001000813

• Whole Exome Sequencing of healthy Spanish individuals - Fastq files

  The need for a detailed catalogue of local variability for the study of rare diseases within the context of the Medical Genome Project motivated the whole exome sequencing of 267 unrelated individuals, representative of the healthy Spanish population.

  Dataset EGAD00001001012

• BLUEPRINT September 2016, ATAC-seq for tonsil, on Genome GRCh38

  ATAC-seq data for 7 sample(s) from tonsil, on Genome GRCh38. 7 run(s), 7 experiment(s), 7 alignment(s). Part of BLUEPRINT (September 2016).

  Dataset EGAD00001002708

• Whole-genome sequencing data for inflammatory breast cancer patients

  This study reports the whole-genome sequencing data for 20 inflammatory breast cancer patients, each of whom has one normal blood sample and one breast tumor sample. Overall, there are 40 files included in this study, in the format of BAM.

  Dataset EGAD00001005749

• single cell RNASEQ files for Mullighan BiTE RNASEQ3

  single cell RNASEQ files for Mullighan BiTE RNASEQ3 paper titled "Tumor intrinsic and extrinsic mechanisms of response and resistance to blinatumomab in relapsed/refractory acute lymphoblastic leukemia"

  Dataset EGAD00001005733

• H3Africa ReMAC Shotgun Metagenomic Phenotype

  Phenotype data for shotgun metagenomic sequencing data of nasopharyngeal fluid for studying nasopharyngeal colonization dynamics with Streptococcus pneumoniae and associated antimicrobial-resistance in a South African birth cohort. https://www.ebi.ac.uk/ena/data/view/PRJEB37312

  Dataset EGAD00001006244

• Breast implant-associated anaplastic large cell lymphoma shallow whole genome sequencing for copy number analysis and Whole exome sequencing data.

  Shallow whole genome sequencing of 29 BIA-ALCL patients for copy number analysis and 24 Alk-negative ALCL samples as control cohort. 7 Whole exome sequencing BIA-ALCL samples.

  Dataset EGAD00001006433

• Clinical data

  This dataset contains demographic, histology, PDL1 IHC, TMB and outcome data (PFS and ORR) for 836 patients, 823 of which had RNAseq, 715 had FMI, with 702 patients having both. The dataset also includes xCell deconvolution scores for patients with RNAseq data.

  Dataset EGAD00001006617

• Genome-wide data for 11 Roma individuals

  This dataset includes genome-wide autosomal array data for 11 Iberian Roma individuals used in the Merchero project.

  Dataset EGAD00001007773

• A Single-cell Atlas of Progressive TKI Resistance in Chronic Myeloid Leukemia

  57 Bone marrow specimens for 5 healthy bone marrow and 24 CML samples profiled with 10X scRNA-seq 5' upon separation using MACS for CD34.

  Dataset EGAD00001007946

• CBD-RAW-REPERTOIRE-B: B cell bulk repertoire sequence files

  fastq and filtered fasta files for B-cell receptor sequencing. For further information regarding this dataset, please contact Rachael Bashford-Rogers at contact@combat.ox.ac.uk.

  Dataset EGAD00001007960

• Single-cell RNA-seq counts and merged data for 28 Hodgkin lymphomas and 5 reactive lymph nodes

  This dataset contains raw count data (10X CellRanger) for 28 Hodgkin lymphoma samples and 5 reactive lymph nodes, and merged data from all samples (RData object) including cell cluster assignments.

  Dataset EGAD00001008270

• RNA-seq for identification of neotranscripts

  This dataset contains RNA-seq data (Fastq files of paired-end data) of 18 patient tumors used for identification of neotranscripts in 18 different types of fusion-driven sarcomas and other cancers as described in Vibert et al., Mol Cell 2022 (PMID: 35550257)

  Dataset EGAD00001008832

• eMERGE Network Genome-Wide Association Study of Red Cell Indices, White Blood Count (WBC) Differential, Diabetic Retinopathy, Height, Serum Lipid Levels, Specifically Total Cholesterol, HDL (High Density Lipoprotein), LDL (Low Density Lipoprotein), and Triglycerides, and Autoimmune Hypothyroidism.

  The electronic Medical Records and Genomics (eMERGE) Network is a consortium of five participating sites (Group Health Seattle, Marshfield Clinic, Mayo Clinic, Northwestern University, and Vanderbilt University) funded by the NHGRI to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 19,000 individuals using EMR-derived phenotypes and DNA from linked Biorepositories. Using electronic phenotyping methods, the consortium used DNA samples from all participating sites to explore the genetic determinants of red cell indices, white blood count (WBC) differential, diabetic retinopathy, height, serum lipid levels, specifically total cholesterol, HDL (high density lipoprotein), LDL (low density lipoprotein), and triglycerides, and autoimmune hypothyroidism as well as using the phenome-wide association study (PheWAS) paradigm to replicate and discover relationships between targeted genotypes with multiple phenotypes. eMERGE led studies for which original genotyping was performed and are included in this merged set: Genome-Wide Association Study on Cataract and HDL in the Personalized Medicine Research Project Cohort, phs000170 Development and Use of Network Infrastructure for High-Throughput GWA Studies, phs000234 Vanderbilt Genome-Electronic Records (VGER) Project: QRS Duration, phs000188 Northwestern NUgene Project: Type 2 Diabetes, phs000237 A Genome-Wide Association Study of Peripheral Arterial Disease, phs000203 Sites and participants include: Vanderbilt University: BioVU, Vanderbilt's DNA databank, is an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses, and represents a key first step in moving the emerging sciences of genomics and pharmacogenomics from research tools to clinical practice. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt's EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations. Marshfield Clinic: The Marshfield Clinic Personalized Medicine Research Project is a population-based biobank in central Wisconsin with more than 20,000 adult subjects who provided written, informed consent to access their medical records and provided a blood sample from which DNA was extracted and plasma and serum stored. In addition to an average of 30 years of medical history data, a questionnaire about environmental exposures, including a detailed food frequency questionnaire, is available to facilitate gene/environment studies. Northwestern University: The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a self-reported questionnaire and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. Group Health(GH)/University of Washington (UW): Aging and Dementia eMERGE study biorepository leverages rich population-based longitudinal data from both electronic medical records and in-depth research data to explore genome wide associations. Participants include Seattle-area members of GH (a large integrated health care system in Washington State) consented and enrolled in 1) the UW Alzheimer's Disease Patient Registry (ADPR) and 2) the Adult Changes in Thought (ACT) study. The ADPR (PI: Eric B. Larson; NIH/NIA U01 AG 006781) is a population-based registry of incident dementia cases designed to identify all new Alzheimer's Disease cases within GH from 1987 to 1996. Medical history, physical, laboratory testing, and neuropsychological testing were performed on all consenting potential cases for determination of dementia status by a consensus conference. The study base of the ADPR population was stable with an attrition rate of less than 1%/year. The ACT study (PI: Eric B. Larson; NIH/NIA U01 AG 006781) is an ongoing community-based cohort study of aging and dementia. The original cohort of 2,581 randomly selected dementia-free members age 65 and older was enrolled in 1994-1996 and expanded by 811 in 2000-2002. Continuous enrollment to maintain a cohort of 2,000 dementia free persons began in 2005. Participants receive biennial assessment including cognitive status determination. The ACT sub-sample is stable; for the original cohort, median enrollment in GH was 19 years prior to joining the ACT study, and 85% of the cohort has ≥10 years of GH enrollment. DNA for the ADPR participants were obtained through a companion study, Genetic Differences in Cases and Controls (PI: Walter Kukull; NIH/NIA R01 AG007584). DNA obtained through both studies were extracted from blood using Gentra Systems Puregene methods. DNA concentration is determined by UV optical density. All samples are checked for quality by 260/280 ratio. For long-term storage, samples are aliquoted and stored at -70°C. Mayo Clinic: The Mayo biobank is a disease-specific biobank for vascular diseases including peripheral arterial disease (PAD). PAD patients were identified from individuals referred to the non-invasive vascular laboratory for lower extremity arterial evaluation. Since 1997, laboratory findings have been recorded into an electronic database employing an in-house software package for data archiving and retrieval; this data becomes part of the Mayo EMR. Patients referred to the center with suspected PAD undergo a comprehensive non-invasive evaluation including the ankle-brachial index (ABI) - the ratio of blood pressure measured in the upper arms divided by blood pressure measured at the ankles. Controls subjects are identified from patients referred to the Cardiovascular Health Clinic for stress ECG. The prevalence of PAD in patients with normal exercise capacity who do not have inducible ischemia on the stress ECG, was <1%. Data regarding risk factors for atherosclerosis such as diabetes, dyslipidemia, hypertension, and smoking are ascertained from the EMR.

  Study phs000360

• Genomic Origins and Admixture in Latinos (GOAL)

  The GOAL Study was designed to comprehensively evaluate the genomic architecture of diverse Hispanic/Latino individuals with origins from the Caribbean, Central and South America, and to understand the impact of this diversity on genetic disease studies. Population structure and admixture are key confounders in genome-wide association and medical resequencing studies. In particular, accounting for difference in ancestry among cases and controls, both in terms of genomic and geographic location, is critical for proper analysis and interpretation of studies with multi- and trans-ethnic samples. Genomic studies of Hispanics/Latinos, the largest and fastest growing minority group in the US, reveal that they are a highly genetically heterogeneous admixed group with immense variation among individuals and populations in the proportions of African, European, and Native American ancestry. Knowledge of the underlying complex genetic structure of US Hispanic/Latino and Caribbean populations is, therefore, essential to ensuring robustness of genotype-phenotype associations and understanding the medical relevance of associated variants across diverse populations in the US and throughout the Americas. Furthermore, since much is known about the African and European migrations into the Americas over the past 500 years, population genetic studies of Hispanics/Latinos serve as an excellent model for developing novel algorithms and approaches for characterizing fine-scale genetic structure of admixed populations, in general. This project extends current studies of population genetic structure in US Hispanics/Latinos by densely genotyping parent-offspring triads from individuals (sampled in the US) of Caribbean-descent from six Latin American countries: Puerto Rico, Cuba, Dominican Republic, Haiti, Honduras and Colombia. This study will provide immediate insights and new statistical methods to improve study design and genetic analysis for medical genomic studies in Hispanics/Latinos, other complex admixed groups, and multi- and trans-ethnic studies.

  Study phs000750

• PROGRESS/ELEMENT DNA Methylation Study

  An extension to the Early Life Exposures in Mexico to Environmental Toxicants (ELEMENT) birth cohort of Mexico City, the Programming Research in Obesity, GRowth, Environment and Social Stress (PROGRESS) Cohort is an ongoing longitudinal pre-birth cohort, established in 2006 in Mexico City, partnering Icahn School of Medicine at Mount Sinai with Harvard University and the National Institute of Public Health in Mexico, which was designed to study the effects of prenatal exposure to toxic metals, air pollution, phthalates, and stress on childhood development. Pregnant women of 18 years of age and older, pregnant for less than 20 weeks of gestation, had no documentation of heart or kidney disease, no use of steroids or anti-epilepsy drugs, no daily alcohol consumption, had telephone access, and planned to live in Mexico city for the following 3 years, and receiving care through the Mexican Social Security System were initially enrolled (n=1,054). In addition to clinical, demographic and exposure data collected, cord blood was collected to interrogate DNA methylation across the genome for over 300 mother-child dyads. Clinical assessments and exposures were captured during several life stages, including prenatal, infant (0-1 year), youth (1-18 years), and adulthood (mother). The PROGRESS cohort added well-documented phenotyping of children for obesity, metabolic dysfunction, respiratory outcomes, and cardiovascular outcomes, as well as measures of air pollutant, personal care/consumer product, non-chemical stress, and metal mixture exposures. No clinical trials were conducted in this cohort. The data collected in this study should provide a unique resource to investigate DNA methylation as it relates to several environmental exposures and adverse cardiometabolic and neurocognitive health in mothers and children from a prospective birthing cohort. For access to demographic, clinical, and exposure data please directly contact study principal investigators.

  Study phs002754

• Center Common Disease Genomics [CCDG] - Cardiovascular: Partners Biobank

  This study is a part of NHGRI's Center for Common Disease Genomics, a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will perform whole genome sequencing of 140K individuals and whole exome sequencing of 225K individuals over the course of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. CAD is the leading cause of death in the world and common variant association studies show that our understanding of the underlying molecular mechanisms is incomplete (e.g, >2/3 of the 63 common variants previously mapped for CAD do not directly relate to known risk factors). CAD is representative of a class of common diseases with onset at middle age. When CAD occurs early in life, there is a stronger inherited component. In addition, there is empirical evidence that a burden of rare coding alleles in individual genes contribute to risk for CAD. Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOCAD_STROKE_FINAL.pdf For this study, The Broad Institute of MIT and Harvard generated genetic data for ~13,500 individuals from the Partners Biobank, including using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array), with 550 samples from patients with myocardial infarction, a type of EOCAD. Partners Biobank, launched in 2010, is a biobank composed of samples from Partners hospitals, including Massachusetts General Hospital and Brigham and Women's Hospital. The Biobank has enrolled >100K individuals to study how genes, lifestyle, and other factors affect people's health and contribute to disease.

  Study phs002018

• Integration of Genomics and Transcriptomics in unselected Twins and in Major Depression

  Our goals are to develop a comprehensive understanding of the genomics of transcription in a population based unselected sample and to discover DNA and RNA biomarkers for major depressive disorder (MDD). This work is essential to developing a more complete understanding of the biological basis of MDD, a common complex trait associated with considerable morbidity, mortality, and personal/societal cost. All biological samples have been collected from well-defined populations, and are now available. First, we conduct a "genetical genomics" or eQTL study of ~800 MZ and ~800DZ twin pairs. Each subject has been assayed for genome-wide SNPs and CNVs and gene expression from peripheral blood sampled under standardized conditions. We determine the genetic architecture (genetic and non-genetic proportions of variance via twin analyses) for every transcript, and the genome-wide associations (i.e., SNP-transcript eQTL pairs). These analyses will be expanded to consider transcriptional modules. The key deliverable is a detailed catalogue of the general and specific architecture of transcription plus raw intensity files. Second, we seek to discover DNA and RNA biomarkers relevant to MDD, capitalizing on the results of a large MDD study with repeated clinical and biological assessments; we have previously shown that PB is a reasonable proxy for CNS expression and employ an advanced modelling framework: (a) Using baseline data, we identify biomarkers for MDD by comparing ~1000 controls with ~1400 MDD cases via comparisons of SNP, CNV, expression transcripts, and transcriptional modules. (b) Using longitudinal data, we contrast gene expression signatures assessed at baseline and two years later in ~200 controls and ~500 MDD cases.

  Study phs000486

• Binding of Epstein Barr Virus EBNA2 Unifies Multiple Sclerosis Genetic Mechanisms

  This study is focused on multiple sclerosis (MS). MS is likely caused by a combination of genetic and environmental factors; however, the mechanisms contributing to these factors remain poorly understood. Epstein-Barr virus (EBV) in particular is a well-established environmental risk factor for MS. We have created a computational algorithm that systematically searches for common molecular mechanisms that might be impacted at multiple MS-associated loci. Using this algorithm, we have discovered that over 40% of MS-associated loci contain MS genetic variants that fall within regions of the human genome occupied by the EBV-encoded EBNA2 protein. The same MS-associated variants also impact gene expression levels of MS-associated genes in EBV-infected B cell lines. Our hypothesis is that allele-dependent binding of EBNA2 and its co-factors explains the allele-dependent risk at many MS genetic loci. Importantly, this hypothesis links the genetic associations of MS to the known molecular roles played by EBV and Notch signaling in disease processes.Subjects with and without MS were recruited into an Institutional Review Board (IRB)-approved protocol through the Cincinnati Autoimmune Registry and Repository. From each subject, DNA from peripheral blood was isolated for whole genome sequencing (WGS). These data will be used to identify genotype-dependent transcriptional regulation in cells assessed from patients and controls. This WGS data was deposited before the full integration of sequence data with other functional genomic data types.From each subject, 90 mL of blood is drawn for isolation of peripheral blood mononuclear cells from which primary B and T cells will be isolated. For each B cell isolation, an EBV-transformed B cell line will be derived.

  Study phs003240

• Enhancing Open Data Sharing for Functional Genomics Experiments: Measures to Quantify Genomic Information Leakage and File Formats for Privacy Preservation

  This study was designed to develop methods that address the privacy risk associated with genetic variants obtained from genomic sequencing experiments. The preponderance of readily available genetic sequencing experiments has enabled the generation of datasets whose target purposes range from the genotyping of individuals for medical and forensic analyses, to the acquisition of molecular information for biological model development. However, by virtue of the experimental procedure, the raw sequences are tagged with small bits of patients' private variant information. In addition, depending on the protocol, these experiments may identify sequences from exogenous species. Raw human and microbial sequences can be analyzed as a whole to learn both general facts about biology, but can also be used to determine sensitive information about an individual. This presents a privacy conundrum for data sharing.To address privacy concerns, we have developed several mathematical and computational approaches to quantify the risk of disclosure of sensitive information from genetic sequence data, and to sanitize the associated reads in a manner that optimally maintains the utility of the data. In addition, we have generated environmental samples containing genetic information from consented individuals to evaluate the risk posed by such data. These samples were then used to assess the efficacy of the computational methods. Human-derived and -associated samples that are damaged or obscured by environmental factors represent the scope of samples used for experimentation in this study. Samples include, but were not limited to, swabs of contacted objects and glass slides coated in saliva from consented individuals. Blood samples were also acquired from the same consented individuals to create gold-standard comparison datasets.

  Study phs003166