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• BLUEPRINT WP10 Quantitative Trait Loci (QTLs) Phase 2 Full Summary Statistics

  BLUEPRINT WP10 Quantitative Trait Loci (QTLs) Phase 2 full summary statistics data include five molecular traits (eQTL, hQTL(H3K27ac), hQTL(H3K4me1), mQTL, and psiQTL) for three primary blood cells (Monocytes, Neutrophils, and T-cells). Each full summary statistics file contains the associations for all tested variants for each phenotype ID.

  Dataset EGAD00001005199

• Sequencing data for the Genomic Autopsy Study

  The .cram files of the Trio or Quad sequencing data used for generation of the genomic autopsy study. This contains a mix of genome sequencing and exome sequencing data for probands and their parents. A subset of families (n=32) did not provide consent to publicly sharing their data.

  Dataset EGAD00001009737

• Dataset of transcriptomic, whole genome and whole exome sequencing to identify predictive biomarkers in pediatric solid tumors

  This Dataset contains whole genome sequencing data for 148 sample, transcriptome sequencing for 66 samples and exome sequencing for 123 samples from pediatric solid tumors. Sequencing was performed on Illumina NovaSeq 6000 and Illumina HiSeq 4000. The sequencing was paired.

  Dataset EGAD00001015701

• Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

  Development of a novel machine learning guided ctDNA detection platform for use in liquid biopsy detection and therapeutic monitoring of solid tumors in several clinical contexts. Included are WGS alignments from our study.

  Study EGAS00001007306

• Whole Exome Sequencing for Colorectal Cancer

  This project was designed to use next generation sequencing technology to screen the protein coding regions of the genome for low frequency variants in a panel of high-risk colorectal adenocarcinoma cases. Blood and cell-line DNA for colorectal cancer patients and a subset of quality control samples that had existing whole exome sequence data were analyzed using Illumina HiSeq sequencers. Samples from this project were from participants in the Women's Health Initiative (WHI) and the Diet, Activity, and Lifestyle Study (DALS).

  Study phs000410

• Circulating Tumor DNA Sequencing Provides Comprehensive Mutation Profiling for Pediatric Central Nervous System Tumors

  Tumor molecular profiling is increasingly important for the diagnosis and clinical management of childhood brain tumors, including diffuse midline glioma (DMG). We established a targeted deep sequencing approach using the TruSight Oncology 500 ctDNA exome panel to detect tumor genomic mutations and copy number variations in circulating tumor DNA from children diagnosed with DMG. In this study, we present the sensitivity, specificity, and clinical implications of our liquid biopsy sequencing approach for tumor genome profiling in children with DMG.

  Study phs003022

• WGS data for EBiSC iPSC lines

  The European Bank for Induced Pluripotent stem cells (EBiSC) is designed to address the increasing demand by iPSC researchers for quality-controlled, disease-relevant research grade iPSC lines, data and cell services. In this study Whole Genome Sequencing was performed on a selection of lines from the project.

  Study EGAS50000000742

• A GWAS for cutaneous leishmaniasis in Brazil

  Our goal was to identify genetic risk factors for cutaneous leishmaniasis (CL) caused by Leishmania braziliensis. Genotyping 2066 CL cases and 2046 controls using Illumina HumanCoreExomeBeadChips provided data for 4,498,586 imputed single nucleotide variants (SNVs). Genome-wide association testing using linear mixed models took account of genetic diversity/ethnicity/admixture. Post-GWAS positional, expression quantitative trait locus (eQTL), and chromatin interaction mapping was performed in FUMA. Transcriptional data were compared between lesions and normal skin, and cytokines measured using flow cytometry and Bioplex assay.

  Study EGAS00001004596

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Tumor infiltration by T cells is paramount for effective anti-cancer immune responses. We hypothesized that the T cell receptor (TCR) repertoire of tumor infiltrating T lymphocytes (TIL/Tc) could determine disease course at different stages in cancer progression. We show that the diversity of the TIL/Tc TCR at baseline is prognostic in various cancers, whereas in metastatic melanoma TIL/Tc TCR clonality at baseline is predictive for activity and efficacy of PD1 blockade immunotherapy.

  Study EGAS00001005201

• Single cell RNA sequencing of normal endometrial derived organoids uncovers novel cell type markers for prognostication

  Endometrial carcinoma, the most common gynecologic cancer, develops from endometrial epithelium which is composed of secretory and ciliated cells. Pathologic classification is unreliable and there is a need for prognostic tools. We used single cell sequencing to study organoid model systems derived from normal endometrial endometrium to discover novel markers specific for endometrial ciliated or secretory cells. We performed single cell sequencing on endometrial and ovarian tumors and found both secretory-like and ciliated-like tumor cells.

  Study EGAS00001004466

• Annotated VCF Files for WGS of ASD Cohort with 68 Individuals from 22 families, enriched for recent shared ancestry

  We performed whole genome sequencing (WGS) in an ASD cohort of 68 individuals from 22 families enriched for recent shared ancestry. Samples were sequenced using Illumina HiSeq X platform, and Variants (single nucleotide variants (SNVs) and insertions or deletions (indels)) were detected using GATK with HaplotypeCaller. Quality control checks for (i) duplicate samples, (ii) samples per platform, (iii) genome call rate, (iv) missingness rate, (v) singleton rate, (vi) heterozygosity rate, (vii) homozygosity rate, (viii) Ti/Tv ratio, (ix) inbreeding coefficient, and (x) sex inference were performed as previously described. Variant call format (VCF) files for SNVs and indels were annotated with ANNOVAR using allele frequencies from the 1000 Genomes project (2015; 1000G), the Genome Aggregation Database (gnomAD), and the Greater Middle East Variome Project (GME).

  Dataset EGAD00001008634

• Investigation of different library preparation and tissue of origin deconvolution methods for urine and plasma cfDNA methylome analysis

  In this study, a single- and a double-stranded library preparation approach was evaluated with respect to their technical biases when applied on cfDNA from plasma and urine. This study thus outlines potential limitations of double-stranded library preparation for methylation analysis of cfDNA especially for urinary cfDNA. While the double-stranded method allows jagged end analysis in addition to TOO analysis, it leads to significant methylation bias in urinary cfDNA, which single-stranded methods can overcome.

  Study EGAS00001007314

• ctDNA multigenic panel for non-small cell lung cancer

  Detection of actionable mutations in liquid biopsies constitute an important tool for management of non-small cell lung cancer (NSCLC) patients in the era of oncology precision medicine. We aimed to evaluate the actionable alterations using a commercial multi-gene panel in circulating tumor DNA (ctDNA) derived from plasma samples of treatment naïve and prior-treated non-small cell lung cancer (NSCLC) patients. For this, we analyze plasma samples of 30 subjects with non-small cell lung cancer.

  Study EGAS50000000643

• cfDNA methylation dataset for colon cancer

  Enzymatic conversion-based methylation sequencing data (EM-seq) for colon cancer used in the MESA study

  Dataset EGAD50000000075

• PASCAL-MID Data Access Committee

  DAC for the center of Personalized Approach to Genome Editing of Stem Cells for Autotransplantation of Monogenic Immunodeficiencies (PASCAL-MID) at Aarhus University and Aarhus University Hospital

  Dac EGAC50000000680

• Pancreatic Cancer NGS WGS data

  Whole genome sequencing data for Pancreatic Cancer Samples exploring the tandem duplicator phenotype

  Study EGAS50000001078

• V4_Colorectal_panel_test

  Targeted gene screen of cell line tumours for testing the new V4 Colorectal gene panel.

  Study EGAS00001001807

• Dataset for B-ALL scRNA-seq

  10x Genomics 5' library scRNA-seq data for 85 B-ALL patients with different subtypes

  Dataset EGAD00001011327

• A98269B

  Whole genome sequencing for single cells for library A98269B 1609 cells; filetype=bam

  Dataset EGAD00001006947

• A96217B

  Whole genome sequencing for single cells for library A96217B 1616 cells; filetype=bam

  Dataset EGAD00001006945

• ChIP-Seq files for PCGP ATRX study

  ChIP-Seq files for PCGP ATRX study paper titled "MYCN Amplification and ATRX Mutations are Incompatible in Neuroblastoma"

  Dataset EGAD00001004429

• WGBS data for Glioblastoma (EGAS00001003953, H016)

  Whole Genome Bisulfite data for human glioblastoma patients, EGAS00001003953. 68 human samples

  Dataset EGAD00001006546

• PACA-CA RNASeq fastq files

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

  Dataset EGAD00001003972

• KiCS cancer panel academic only data

  This data set contains KiCS cancer panel data for academic and for-profit use.

  Dataset EGAD00001009733

• Comparison of Custom Capture for Targeted Next Generation DNA Sequencing

  Targeted, capture-based DNA sequencing is an economical way to sequence a customized region of the genome. Several targeted sequencing kits are available, but the efficacies of these kits have not been compared. We appraised four targeted DNA technologies for next generation sequencing, considering on-target sequencing, uniformity, and single nucleotide variation and copy number variation discovery. The technologies which utilized sonication to fragment genomic material showed impressive uniformity of capture. The other two had shorter preparation times, but sacrificed uniformity. One of those technologies, which needs transposase to fragment genomic material, has a weakness that requires all samples be pooled and the final one, which uses restriction enzyme digestion, is limited depending on restriction enzymes digest sites. Naturally, all technologies showed some concordance for calling SNVs, the kits that used restriction enzymes or transposase missed several SNVs, due, in large part, to lack of coverage. All technologies showed high integrity for copy number variant calling when compared to SNP arrays. This study aids laboratories in their decision of the proper technology to use for their intended applications.

  Study phs000811

• A Multi-Gene Mutation Classification of 468 Colorectal Cancers Reveals a Prognostic Role for APC

  Colorectal cancer (CRC) is a highly heterogeneous disease, for which prognosis has been relegated to clinic-pathologic staging for decades. There is a need to molecularly stratify subpopulations of CRC to better predict outcome and assign therapies. Here we report targeted exome sequencing of 1,321 cancer-related genes on 468 tumor specimens, which identified a subset of 17 genes that best classify CRC, with APC (Gene ID: 324) playing a central role in predicting overall survival. APC may assume 0, 1, or 2 truncating mutations, each with a striking differential impact on survival. Tumors lacking any APC mutation carry a worse prognosis than single APC mutation tumors, but tumors with two APC mutations and KRAS (Gene ID: 3845) and TP53 (Gene ID: 7157) mutations confer the poorest survival among all the subgroups examined. Our study demonstrates a substantial prognostic role for APC and suggests that sequencing of APC may have clinical utility in the routine staging and potential therapeutic assignment for CRC.

  Study phs001111

• The National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis (CLEAR)

  The Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis (CLEAR) Registry and Repository, supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), was established in 2000 to provide a resource for the scientific community to explore genetic and non-genetic factors affecting rheumatoid arthritis (RA) occurrence and outcomes in African Americans. The long term objective is a database and a repository of 1,100 RA and 550 matched healthy African-American subjects. This CLEAR Registry and Repository has two arms: a longitudinal arm for subjects with early RA (enrollment from 2000 to 2005) and a cross-sectional arm for subjects with any disease duration (enrollment from 2006 to 2012). CLEAR has two components: a database and a repository. The database contains extensive demographic, socioeconomic, clinical and radiographic (radiographs of hands and feet) information and bone mineral density data from DEXA scans. The repository contains genomic DNA, plasma and serum on most of the participants. Participants in CLEAR II had RNA isolated from peripheral blood cells.

  Study phs001360

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Hispanic Community Health Study/Study of Latinos (HCHS/SOL)

  Cohort DescriptionHispanic Community Health Study/Study of Latinos (HCHS/SOL) is an ongoing population-based prospective cohort study of 16,415 community dwelling Hispanic/Latino adults aged 18-74 years at baseline, recruited from four urban field centers with large populations of Hispanics/ Latinos (Bronx, NY; Chicago, IL; Miami, FL; and San Diego, CA). The primary goals of the HCHS/SOL are to describe: (1) the prevalence and incidence of cardiovascular, pulmonary, and other major chronic conditions (2) the risk and/or protective factors associated with these conditions; and (3) the relationships between the initial sociodemographic and health profiles and future health events in the target population. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 9817 HCHS/SOL participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 7536 HCHS/SOL participants in C4R. Derived data includes 43 variables for up to 11182 HCHS/SOL participants in C4R. Phenotype data includes 113 variables for up to 11182 HCHS/SOL participants in C4R.

  Study phs002908

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Northern Manhattan Study (NOMAS)

  Cohort Description The Northern Manhattan Study (NOMAS) is a study of the population of Washington Heights in Northern Manhattan. The ongoing study, which began in 1990, has enrolled over 4,400 people, some of whom have suffered a stroke or related neurological syndromes. As the cohort aged, the specific aims grew to include not only vascular determinants of stroke but also cognitive decline, mild cognitive impairment (MCI) and dementia. The overall goal of NOMAS is to investigate stroke risk factors in different race-ethnic groups. NOMAS is also committed to developing better stroke prevention programs to improve the health of the community. The Hispanic population in Northern Manhattan is largely Dominican, along with Puerto Rican, Cuban, and Central and South American components.Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 887 NOMAS participants in C4R Wave 2 questionnaire data includes 448 variables for up to 815 NOMAS participants in C4R Derived data includes 43 variables for up to 995 NOMAS participants in C4R Phenotype data includes 113 variables for up to 995 NOMAS participants in C4R

  Study phs003028

• The Innate Immune Response as a Therapeutic Target for Cutaneous Leishmaniasis

  The overall goal of the proposed project is to identify innate host functions that contribute to cure or failure during antileishmanial drug therapy, and their related biomarkers. Results from this project enabled the identification of host-specific predictive and prognostic signatures of therapeutic responsiveness, and the bases for rational selection of host-targeted therapeutics that redirect inflammation and revert pathogenicity. Through sequential transcriptomic profiling of blood monocytes (Mo), neutrophils (Nφ), and eosinophils (Eφ) over the course of systemic treatment with meglumine antimoniate, we discovered that a heightened and sustained Type I interferon (IFN) response signature is a hallmark of treatment failure (TF) in Cutaneous Leishmaniasis (CL) patients. The transcriptomes of pre-treatment, mid-treatment and end-of-treatment samples were interrogated to identify predictive and prognostic biomarkers of TF. Results from this study instigate the evaluation of Type-I IFN responses as new immunological targets for host-directed therapies for treatment of CL, and highlight the feasibility of using transcriptional signatures as predictive biomarkers of outcome for therapeutic decision making.

  Study phs003545

• Genome-wide analyses of cell-free DNA for therapeutic monitoring of patients with pancreatic cancer

  Determining response to therapy for patients with pancreatic cancer can be challenging. We evaluated methods for assessing therapeutic response using cell-free DNA (cfDNA) in plasma samples from 40 patients with metastatic pancreatic cancer as part of the CheckPAC trial (NCT02866383). Patients were evaluated before and after initiation of therapy using tumor-informed plasma whole-genome sequencing (WGMAF), and genome-wide cfDNA fragmentation profiles and repeat landscapes (ARTEMIS-DELFI). Of those assessed with WGMAF, molecular responders had a median overall survival (OS) of 319 days compared to 126 days for non-responders (HR=0.29, 95% CI=0.11–0.79, p=0.011). For ARTEMIS-DELFI, patients with low scores after therapy initiation had a longer median OS than patients with high scores (233 days versus 172 days, HR=0.12, 95% CI=0.046-0.31, p<0.0001). We validated ARTEMIS-DELFI in a separate cohort of 40 patients with pancreatic cancer who were part of the PACTO trial (NCT02767557). These analyses suggest that non-invasive mutation and fragmentation-based cfDNA approaches can identify therapeutic response of individuals with pancreatic cancer.

  Study EGAS50000000923

• BAMSE (Swedish abbreviation for Children, Allergy, Milieu, Stockholm, Epidemiology)

  The BAMSE (Swedish abbreviation for Children, Allergy, Milieu, Stockholm, Epidemiology) study is an ongoing longitudinal, population-based prospective birth cohort including 4,089 children born between 1994 and 1996 in Stockholm, Sweden. The cohort was initially designed to study risk factors for asthma, allergic diseases and lung function in childhood, and to study factors of importance for prognosis at already established disease.Questionnaires on respiratory symptoms and medication were answered at age of 1, 2, 4, 8 and 16 years. Response rates ranged from 96-82% at each occasion with very minor selection bias over the years. Exposure to air pollutants and other environmental factors has been mapped since birth.At the 8 and 16 year follow-up, spirometry and FeNO measurements were performed and at the latter, impulse oscillometry was measured. Blood samples (including plasma) from around 2,500 children were taken at 4, 8 and 16 years and have been analyzed for different IgE-ab and biomarkers. Genome-wide genetic, global methylation and transcriptomic data exist on a subset of the children.

  Study EGAS00001002746

• A combined circulating tumor DNA and protein biomarker-based liquid biopsy for the earlier detection of pancreatic cancer

  The earlier diagnosis of cancer is one of the keys to reducing future cancer deaths. Here we describe our efforts to develop a non-invasive, blood test for the detection of pancreatic ductal adenocarcinoma. We combined blood tests for KRAS gene mutations with carefully thresholded protein biomarkers to determine whether the combination of these markers was superior to any single marker. The cohort tested included 221 patients with resectable pancreatic ductal adenocarcinoma and 185 control patients without known cancers. KRAS mutations were detected in the plasma of 66 patients (30%) and every mutation found in the plasma was identical to that subsequently found in the patients' primary tumor (100% concordance). The use of KRAS in conjunction with two thresholded protein biomarkers (CA19-9 and prolactin) increased the sensitivity to 67%. Only one of the 185 plasma samples from the control cohort were positive for any of the three markers (99.5% specificity). This combinatorial approach may prove useful for the earlier detection of many cancer types.

  Study EGAS00001002444

• An Isogenic Cell Line Panel for Sequence-based Screening of Targeted Anti-cancer Drugs

  We describe the creation and characterization of an isogenic cell line panel representing common cancer pathways, with multiple features optimized for high-throughput screening. More than 1,800 cell lines from three normal human cells were generated using CRISPR-technologies. Surprisingly, we discovered most of these lines did not result in complete gene inactivation, despite integration of sgRNA at the desired genomic site. However, a subset of the lines harbored true, biallelic disruptions of the targeted tumor suppressor gene, yielding a final panel of 100 well-characterize lines covering 19 pathways frequently subject to loss of function in cancers. This panel included genetic markers optimized for sequence-based ratiometric assays for drug-based screening assays. To illustrate the potential utility of this panel, we developed a multiplexed high-throughput screen that identified Wee1 inhibitor MK-1775 as a selective growth inhibitor of cells with inactivation of TP53. These cell lines and screening approach should prove useful for researchers studying a variety of cellular and biochemical phenomena

  Study EGAS00001005974

• dbGaP Collection: NHLBI Heart Failure Related dbGaP Data (No IRB requirement)

  The National Heart, Lung, and Blood Institute (NHLBI) Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research has concluded. The NHLBI will continue to make this collection of data available to the research community.Past information regarding the Data Collection for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research is below.The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health (NIH), is inviting novel Solutions for the NHLBI Big Data Analysis Challenge: Creating New Paradigms for Heart Failure Research. The goal of the challenge is to foster innovation in computational analysis and machine learning approaches utilizing large-scale NHLBI-funded datasets to identify new paradigms in heart failure research. The challenge aims to address the need for new open source disease models that can define sub-categorizations of adult heart failure to serve as a springboard for new research hypotheses and tool development in areas of heart failure research from basic to clinical settings. NHLBI has a history of making considerable investments in the creation of deep data resources including: long-standing, deeply-phenotyped epidemiological cohorts, innovative clinical trials, and large-scale precision medicine efforts that have generated whole genome sequencing and "other omics" data for more than one-hundred thousand individuals. To provide challenge participants with streamlined access to data across NHLBI's numerous studies containing heart failure data, the NHLBI has created this dbGaP study collection. Data access for this collection is controlled by NHLBI's Data Access Committee. Challenge participants are required to follow the use restrictions and acknowledgement instructions from the original dataset(s). Please note that the data in this collection are not harmonized across studies or otherwise altered from the original study. The NHLBI Big Data Analysis Challenge: Heart Failure Data Collection contains all NHLBI studies currently in dbGaP that contain data that may be relevant to research on heart failure. The studies in this collection are approved for General Research Use (GRU), Health/Medical/Biomedical Use (HMB), or Disease-Specific Use (DS) that permits research on heart failure. These studies span a variety of study designs, inclusion and exclusion criteria, sample sizes, and provide a wide breadth and depth of phenotype data on study participants. The available genomic data in these studies also varies, including genotyping arrays, sequencing (targeted, exome, whole genome), and additional -omic data (e.g., RNA or metabolite profiles). Please refer to each study's individual accession page to learn more about how study data were collected. Challenge participants are reminded that in addition to dbGaP, NHLBI's Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC) contains other studies that have collected data relevant to heart failure and may wish to utilize BioLINCC data in the development of their Solution. Please refer to the individual accession page for each study in this collection to learn more about the history of each study.

  Study phs001991

• Additional Methylation files for Roussel-ATRT-TM

  Additional Methylation files for Roussel-ATRT-TM paper titled &quot;Atypical teratoid/ rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities&quot;

  Dataset EGAD00010002495

• DAC for TFHL single-cell analysis project at Department of Hematology, University of Tsukuba

  DAC for study of tumor heterogeneity and immune-evasive microenvironment in T follicular helper cell lymphomas

  Dac EGAC50000000201

• COMPASS Next Generation Sequencing WGS data

  Whole genome sequencing data for Pancreatic Cancer Samples from the COMPASS clinical trial

  Study EGAS50000001091

• Mucosal 16S metadata

  Metadata for 16S-V4 rRNA gene sequence data for intestinal biopsies from NCT02749630 trial participants.

  Dataset EGAD00001008823

• A95673A

  Whole genome sequencing for single cells for library A95673A 1446 cells; filetype=bam

  Dataset EGAD00001006941

• Data files for CONSERTING

  Data files for CONSERTING (WGS)

  Dataset EGAD00001001352

• CUTRUN files for Klco-NUP98 data

  CUTRUN files for paper titled "Fusion oncoproteins and cooperating mutations define disease phenotypes in NUP98-rearranged leukemia"

  Dataset EGAD00001015478

• Targeted sequencing analysis for MDS with HSCT

  Targeted capture sequencing for cases with MDS who were subjected to unrelated bone marrow transplantation via Japan marrow donor program

  Dataset EGAD00001003118

• RNA data for MMML (EGAS00001002422)

  RNA sequencing data for MMML (3 tumor samples and 1 gcbcell)

  Dataset EGAD00001003285

• WGS files for Mullighan_GL_reALL

  WGS files for Mullighan_GL_reALL paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001005506

• WXS files for Mullighan_GL_reALL

  WXS files for Mullighan_GL_reALL paper titled "Mutational landscape and patterns of clonal evolution in relapsed pediatric acute lymphoblastic leukemia"

  Dataset EGAD00001005509

• Gene Expression Signatures in CATHGEN

  Case control cohort: The details have been previously published: American Heart Journal. 2010;160:371-379 e372. Briefly, a nested case:control cohort of CATHGEN participants who had experienced death or MI (n = 250) after their index catheterization and age-, sex-, and race-matched controls (n = 250) who were free of death/MI &#62; 2 years after cardiac catheterization was identified as part of the MURDOCK Horizon 1 Cardiovascular Disease Study.21 Sufficient RNA for microarray analysis was available in 447 members of this cohort. Observational cohort: 224 sequential CATHGEN samples were selected for whole blood RNA analysis, of which, 191 had sufficient RNA for microarray analysis.

  Study phs000551

• Genetics of Pigmentation in Eastern and Southern African Populations Study

  The goal of this study was to identify genes and loci associated with pigmentation in African populations. It comprises 1,593 participants from Ethiopia, Tanzania, and Botswana. Sexes are evenly represented (768 males and 825 females) and self reported ages ranged from 18 to 103. Mean age was used for individuals without ages. For each participant, a DSM II color meter was used to measure underarm skin reflectance in triplicate. These measures averaged and converted to a melanin index (MI = 100 x log10(1/(x/255)). All individuals were included in a genome wide scan that accounted for age, sex, and genetic relatedness.

  Study phs001396

• Estonian Biobank | Estonian Genome Center, University of Tartu

  The Estonian Biobank is the population-based biobank of the Estonian Genome Centre of University of Tartu. The biobank is conducted according to the Estonian Gene Research Act and all participants have signed broad informed consent. The cohort size is currently 51,535 people from 18 years of age and up. Metabolite concentrations (over 110; NMR and MS) are available for about 12,000 subjects; metabolic follow-up has been done for more than 2000 donors. GWAS has been performed on 20,000 subjects with different Illumina arrays and 2,500 have whole exomes and 2,400 full sequence. The data for the 2,400 fully sequenced samples is available through dbGaP.

  Study phs001230

• Sensitive urothelial cancer detection via high volume urine DNA analysis

  Cystoscopy and imaging are the gold standard for urothelial cancer (UC) detection and surveillance, but cystoscopy is an uncomfortable procedure associated with adverse effects and a low diagnostic yield as only 10% of hematuria patients have UC. Urine tumor DNA (utDNA) is a non-invasive UC biomarker that has suffered from poor sensitivity for Ta stage tumors (<80%). We hypothesized that high urine volume analysis with a multi-gene panel could overcome these limitations, and developed a 100 mL utDNA laboratory platform (UroScout) that analyzes 25 commonly mutated UC genes and 8 copy number-altered loci for somatic alterations to detect UC.

  Study EGAS50000000630