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• WGS data for MMML for Study EGAS00001002198

  Whole genome sequencing data for MMML (12 tumor/control pairs)

  Dataset EGAD00001003208

• WGS data for MMML for Study EGAS00001002198

  Whole genome sequencing data for MMML (cell_line)

  Dataset EGAD00001003210

• WGS data for MMML for Study EGAS00001002199

  Whole genome sequencing data for MMML (24 tumor/control pairs), fastq-files

  Dataset EGAD00001003276

• Computational approach to discriminate human and mouse sequences in patient-derived tumour xenografts

  Whole Exome Sequencing was performed in a dilution series containing known amounts of human and mouse DNA, 3x 100% human 0% mouse, 2x 90/10, 3x 50/50, 2x 25/75 and 3x 0/100. A set of breast cancer clinical samples, matched normal tissue and matched PDTXs (total number = 14) were also analysed. Paired-end 75bp sequences for the dilution series and paired-end 125bp for the clinical samples were obtained on Illumina HiSeq2500; fastq files are provided. A triplicate analysis of the transcriptome using RNA-seq was also performed for the Universal Human RNA Reference and the Universal Mouse RNA Reference samples. Paired-end 150bp fastq files obtained on Illumina HiSeq4000 are provided.

  Dataset EGAD00001003800

• ENU-NCI-H508-Cetuximab-SecondRound

  Cetuximab is a targeted monoclonal antibody against the epidermal growth factor receptor (EGFR) which is used therapeutically for the treatment of KRAS wild-type colorectal cancer (CRC). The Cetuximab sensitive KRAS wild-type CRC cell line NCI-H508 has been treated with a fixed concentration of ENU for 24 hours and then selected with Cetuximab until drug resistant clones were ready to be picked and grown up as sub-clones of the parental cell line. These will have genes causally implicated in cancer sequenced to identify common point mutations in multiple independently derived drug resistant clones as a forward genetic screen for mechanisms of resistance to Cetuximab in CRC

  Dataset EGAD00001002065

• Rapid Acceleration of Diagnostics - Digital Health Technologies (RADx-DHT): Digital Health Solutions for COVID-19: COVID Community Action and Research Engagement (COVID-CARE)

  Vibrent Health will expand the Vibrent Digital Health Solutions Platform (DHSP) implementation to additional populations among diverse user groups for additional validation of the technology's performance, usability, and reliability in refinement of analytics generating predictive algorithms for infection and that support individual, organizational, community and societal-level decision-making in the COVID-19 pandemic response. This includes the aims to innovate a technology that can differentiate between COVID-19 and flu (or other respiratory illness); develop and test a novel WIFI-based contact tracing tool using a University’s enterprise WIFI system and software release of augmented contact tracing capabilities in Vibrent's DHSP; and develop a full technical integration approach and strategy to support data exchange between this solution and the NCI data hub.DOI: https://rapids.ll.mit.edu/10.57895/ravs-1b57

  Study phs002533

• Minnesota Center for Twin and Family Research (MCTFR) Genome-Wide Association Study of Behavioral Disinhibition

  This is an epidemiological study of substance abuse and related psychopathology in which the subjects have been drawn from the Minnesota Center for Twin and Family Research (MCTFR). The MCTFR is a large, ongoing, family-based study. It is in part a longitudinal study of two cohorts of adolescent twins and their parents. It additionally includes a parallel longitudinal study of adolescent adoptive siblings, biologically related siblings, and their parents. Over 1500 twin families and 350 adoptive and biological sibling families have been studied, with follow-up assessments occurring approximately every 3 years. The MCTFR gathered detailed, standardized data on study participants including DSM-IIIR and DSM-IV diagnostic interview and questionnaire data. For the Genome-Wide Association Study of Behavioral Disinhibition, parental intake data plus that adolescent data gathered closest to the children 17th birthday (between ages 16.5 and 21) was used.

  Study phs000620

• Center for Common Disease Genomics (CCDG) - Cardiovascular: Cleveland Clinic Cohort

  The National Human Genome Research Institute (NHGRI) has funded the Centers for Common Disease Genomics (CCDG), a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to common disease phenotypes and to better understand the general principles of genomic architecture underlying common, complex inherited diseases. This study contains variant calls derived from the whole genome sequence data of an early-onset coronary artery disease case-control cohort collected by the Cleveland Clinic. Case status was assigned based on the presence of myocardial infarction, coronary artery stenosis greater than 70% in at least one coronary artery, and/or revascularization (coronary angioplasty with or without stent placement or coronary artery bypass grafting) at an early age. For these samples, "early age" is defined as men 60 years of age or younger and women 70 years of age or younger.

  Study phs001871

• Yale Center for Mendelian Genomics (YCMG)

  From 2012-2021, Yale University was home to one of four national centers created by the National Institutes of Health (NIH) to study the genetics of rare inherited diseases. Researchers at Yale University, University of Washington, the Broad Institute and a center operated jointly by Baylor University and Johns Hopkins University analyzed the genomes of thousands of patients who suffer from more than 6,000 rare Mendelian disorders affecting more than 25 million individuals in United States. The Centers for Mendelian Genomics (CMG) applied next-generation sequencing and computational approaches to discover the genes and variants that underlie Mendelian disorders. The discovery of new genes that cause Mendelian conditions expanded our understanding about their biology to facilitate their diagnosis, and potentially indicate new treatments. The CMG provided free exome sequencing and analysis to collaborating investigators for qualified phenotypes.

  Study phs000744

• The Surveillance Monitoring for ART Toxicities (SMARTT) and the Women and Infants Transmission Study (WITS)

  Zidovudine (ZDV) is a nucleoside reverse transcriptase inhibitor (NRTI) which competitively inhibits HIV reverse transcriptase and is incorporated into the viral DNA, resulting in DNA chain termination. It was the first approved antiretroviral medication used for preventing HIV transmission from mother to child. However, in vitro and animal studies have suggested genotoxicity of ZDV and no study has evaluated potential impact of in utero ZDV exposure using genomic sequencing technologies. In this study, we investigate markers of genomic damage detected in peripheral blood mononuclear cell samples obtained from 91 ZDV-exposed and, for comparison, 94 NRTI-unexposed HIV-uninfected children born to HIV-infected mothers during the first week after birth. We utilize high-throughput DNA sequencing (whole exome sequencing) and genotype array methods to comprehensively identify potential clonal somatic single nucleotide variants (SNVs) and large acquired copy number alterations (SCNAs) related to ZDV exposure.

  Study phs002061

• A Human Lymphoma Organoid Model for Evaluating and Targeting the Follicular Lymphoma Tumor Immune Microenvironment

  Heterogeneity in the tumor microenvironment (TME) of follicular lymphoma (FL) can affect clinical outcomes. We developed a new organoid culture method for cultivating patient-derived lymphoma organoids (PDLOs), which include cells from the native FL TME. We generated organoids from 12 FL patients at diagnosis, clinical progression, or relapse. These organoids were profiled with targeted DNA sequencing and mRNA sequencing. We evaluated the stability of organoids in culture at serial weekly timepoints (D0, D7, D14, D21). We treated organoids with CD19:CD3 or CD20:CD3 bispecific antibodies or unconjugated anti-CD20, anti-CD19, and anti-CD3 as a control, and profiled DNA/RNA at D11 to evaluate treatment response. This system is intended as a platform for advancing precision medicine efforts in FL through patient-specific modeling, high-throughput screening, TME signature identification, and treatment response evaluation.

  Study phs003410

• Efficacy of Ustekinumab Followed by Abatacept for the Treatment of Psoriasis Vulgaris (PAUSE)

  Psoriasis is a chronic immune disease of the skin and joints that affects about 2% of the population. The most common form of psoriasis is plaque psoriasis, also called psoriasis vulgaris. A variety of drugs, including biologics, are available for treatment of moderate to severe psoriasis. When biologic agents are stopped, psoriasis can return (relapse) and often requires the biologic to be restarted and continued. No treatment program has been identified to prevent relapse of psoriasis. The study design has a lead-in period of weight-based ustekinumab treatment, with all participants receiving either 45 mg ustekinumab ( 100 kg) administered subcutaneously at weeks 0 and 4. At week 12, participants will be assessed for a Psoriasis Area and Severity Index (PASI) 75 response to ustekinumab. Participants who do not achieve a PASI 75 score will be discontinued from the investigation and permitted to seek standard therapy.

  Study phs003395

• Raw human sequencing data for “Characterization of intestinal immune responses in generalized human and murine lipodystrophy”

  This dataset contains raw FASTQ files generated from peripheral blood and intestinal biopsy samples collected for the study “Characterization of intestinal immune responses in generalized human and murine lipodystrophy.” Peripheral blood sequencing was performed on samples from three healthy donors as controls and from a patient with acquired generalized lipodystrophy and Crohn’s disease (AGLCD) at two distinct timepoints. Intestinal biopsy–derived immune cells were sequenced from three individuals with Crohn’s disease as disease controls, as well as from the AGLCD patient (single timepoint). The data include paired-end FASTQ files derived from single-cell RNA sequencing and T-cell receptor repertoire profiling, enabling analyses of immune composition, transcriptional states, and clonal T-cell expansion. All data are controlled-access human genomic datasets and require appropriate authorization for secondary use.

  Study EGAS50000001517

• Comprehensive benchmarking of methods for mutation calling in circulating tumor DNA

  This study provides a comprehensive benchmarking resource for somatic variant detection in cell-free DNA (cfDNA) from cancer patients. Longitudinal plasma samples from colorectal and breast cancer cohorts were selected to create patient-matched dilution series spanning ultra-low to high circulating-tumour-DNA (ctDNA) fractions, while preserving each individual’s germline and clonal haematopoiesis background. Deep whole-genome sequencing (150×) and ultra-deep whole-exome sequencing (2,000×) generated a reference call set of ~37,000 single-nucleotide variants and ~58,000 insertions/deletions. These data enabled systematic evaluation of nine somatic variant callers across variable ctDNA levels and sequencing depths, and were further used to explore machine-learning–guided parameter tuning. The resulting dataset offers an openly accessible framework for developers and clinicians to assess and optimize somatic variant calling in liquid biopsy applications.

  Study EGAS50000001313

• Multimodal epigenetic sequencing analysis of cell-free DNA identifies biomarkers for ALS diagnosis and progression

  The role of the circulating epigenome in ALS remains understudied. We aim to develop diagnostic and prognostic blood-based biomarkers for Amyotrophic Lateral Sclerosis (ALS) by profiling methylome signatures in circulating cell-free DNA (cfDNA) in 20 sporadic ALS cases, 10 C9orf72-associated ALS cases, 10 asymptomatic C9orf72 expansion carriers, and 21 healthy controls using targeted enzymatic methyl-sequencing (EM-seq) of ~4 million CpG loci. We detected numerous differentially methylated genes, including several implicated in ALS risk and pathobiology, and integrated multiple epigenetic features with our Multimodal Epigenetic Sequencing Analysis (MESA) algorithm, achieving an ROC AUC of 0.91 and detecting ~70% of ALS cases at ~100% specificity. Methylation at a subset of loci also correlated with clinical progression and cerebrospinal-fluid neurofilament levels, supporting the potential of cfDNA-based biomarkers for ALS diagnosis and monitoring.

  Study EGAS50000001267

• H3Africa Chip Design - Aim of designing a cost-effective GWAS chip with content appropriate for use in genomics studies of individuals from the African continent.

  Since it is recognized that currently available chips may not be ideally suited to studying African populations, the H3Africa Genome Analysis working group undertook the task of designing a cost-effective GWAS chip with content appropriate for use in genomics research studies of individuals from the African continent. To address gaps in sequence data for some of the African populations being studied in H3Africa projects, a high coverage whole genome sequence dataset was generated at the Baylor College of Medicine with samples provided by H3Africa PIs and collaborators, funded by the National Institutes of Health. This dataset includes 350 high coverage and 160 medium coverage whole genome sequences from 348 populations. The data is accompanied by minimal metadata, including country, ethnic group and sex.

  Study EGAS00001002976

• A Unifying Paradigm for Transcriptional Heterogeneity and Squamous Features in Pancreatic Ductal Adenocarcinoma

  Pancreatic cancer expression profiles largely reflect a classical or basal-like phenotype. The extent to which these profiles vary within a patient is unknown. We integrated evolutionary analysis and expression profiling in multiregion sampled metastatic pancreatic cancers, finding that squamous features are the histologic correlate of an RNA-seq defined basal-like subtype. In patients with coexisting basal/squamous and classical/glandular morphology, phylogenetic studies revealed that squamous morphology represented a subclonal population in an otherwise classical/glandular tumor. Cancers with squamous features were significantly more likely to have clonal mutations in chromatin modifiers, intercellular heterogeneity for MYC amplification, and entosis. These data provide a unifying paradigm for integrating basal-type expression profiles, squamous histology, and somatic mutations in chromatin modifier genes in the context of clonal evolution of pancreatic cancer.  

  Study EGAS00001003974

• Identification of neoantigen from MSI-CRC patient derived organoids and its application for targeting by autologous T cells

  Targeting neoantigens expressed only by tumor cells enable tumor destruction without unexpected damages to healthy tissues. Here, we identified neoantigens from microsatellite instable (MSI) colorectal cancer (CRC) patient-derived organoids by genomics and immunopeptidomics approches. The neoantigens in this study were predicted from frame-shift mutation by whole-genome sequencing and confirmed its presentation on organoids surface class I HLA molecules by mass spectrometry. We utilized these neoantigens to isolate neoantigen-specific CD8 T cells from autologous PBMC, and proved tumor organoids killing ability of the CD8 T cells, whereas it did not attack normal organoids. This study provides a platform to identify neoantigen from patient-derived cancer organoids and a model to validate T cell recognition, which could be useful for adoptive CD8 T cell transfer treatment for MSI-CRC patient.

  Study EGAS00001006633

• scRNAseq of colonic organoids derived from biopsies taken from healthy human individuals treated with IL22

  scRNAseq dataset of colonic organoids derived from epithelium from biopsies taken from three healthy human individuals. The organoids have either been grown in standard conditions (control) or treated with IL22 (treated). Includes 6 samples in total, one control from each individual (ctrl1, ctrl2, ctrl3) and one treated from each (treat1, treat2, treat3). The samples have been multiplexed using the antibody hashing technique. The 6 samples have been pooled into the one organoids sample. In order to analyse the raw files, they have to be demultiplexed first. Information necessary for demultiplexing, as well as which files belong to which sample, can be found in the map_file.csv, attached to each sample. Dataset includes raw Fastq files and processed csv count matrices. Fastq files are divided into HTO (hashtag) and RNA (transcriptome) files. HTO has one index (I1) and two read (R1, R2) files and RNA has two index (I1, I2) and two read (R1, R2) files. The fastq files are for the pooled (organoids) sample and need to be demultiplexed. Count matrices contain comma-separated values with cell barcodes as column names and gene names as row names. Since count matrices have been created after the demultiplexing step, there’s one matrix for each of the 6 individual samples. scRNA-seq data from human colon organoids was analysed in the same manner as for the Colitis dataset, apart from the following changes. Data was generated with the Cell Hashing technique, which uses oligo-tagged antibodies against surface proteins to barcode single cells. This allows for samples to be multiplexed together and run in a single experiment. The data was demultiplexed using the HTODemux() function from Seurat (Hao et al., 2021).

  Dataset EGAD00001010168

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004413

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004414

• Open Targets 020 Epigenomes of Cell Lines (2018-10-23)

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard & complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target & compound studies to primary human cells and tissues from both healthy volunteers & patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2018-10-23.

  Dataset EGAD00001004416

• 13 WGS and 8 TCS data of ENKL patients treated with pembrolizumab.

  Whole-genome sequencing (WGS) was performed for 13 pairs of tumor-normal samples from patients diagnosed with NKTL. Genomic DNA from tumor tissue was extracted with QIAamp DNA Mini Kit. The DNA for the matching normal was obtained from blood or buccal swabs and purified by Blood and Cell Culture DNA Mini kit or E.Z.N.A. Tissue DNA Kit (Omega Bio-tek) according to manufacturer’s instructions. The quantity and quality were assessed by Quant-iT PicoGreen dsDNA Assay Kit (Invitrogen) and agarose gel electrophoresis. All sequencing libraries were prepared using TruSeq Nano DNA Library Prep Kit (Illumina). Paired-end sequencing was performed on Illumina HiSeq 2000 or HiSeq X Ten as 2x101 bp or 2x151 bp, respectively. 8 NKTL FFPE specimens were screened for somatic mutations using deep targeted capture sequencing (TCS). FFPE rolls or slides were extracted using QIAamp DNA FFPE Tissue kit (QIAGEN). The FFPE genomic DNA was treated with NEBNext FFPE DNA Repair Mix and assessed by Quant-it PicoGreen dsDNA Assay Kit (Invitrogen). The library was generated from 10-200 ng DNA with SureSelectXT Low Input Target Enrichment System for Illumina Paired-End Sequencing Library (Agilent Technologies) according to manufacturer’s instructions. RNA based probe was designed with SureDesign (Agilent Technologies) to target-capture 140 genes. Next, the captured libraries were pooled in equimolar concentration and sequenced on Illumina Novaseq 6000 platform with SP or S1 chip. Reads aligning to 40 selected genes were isolated post-alignment for this submission. Prefix used in filenames: T - Tumor samples N - Matched-Normal samples

  Dataset EGAD00001004140

• RNA-seq as a tool for evaluating human embryo competence

  The majority of embryos that are created through IVF do not implant. It seems plausible that rates of implantation would improve if we had a better understanding of molecular factors affecting embryo competence. Currently, the process of selecting an embryo for uterine transfer utilizes an ad-hoc combination of morphological criteria, the kinetics of development, and genetic testing for aneuploidy. However, no single criterion can ensure selection of a viable embryo. In contrast, RNA-sequencing of embryos could yield highly dimensional data, which may provide additional insight and illuminate the discrepancies among current selection criteria. Indeed, recent advances enabling the production of RNA-sequencing (RNA-seq) libraries from single cells have facilitated the application of this technique to the study of some transcriptional events in early human development. However, these studies have not assessed the quality of their constituent embryos relative to commonly used embryological criteria. Here, we perform proof-of-principle advancement to clinical selection procedures by generating high quality RNA-seq libraries from a trophectoderm biopsy as well as the remaining whole embryo. We combine state-of-the-art embryological methods with low-input RNA-seq to develop the first transcriptome-wide approach for use in future predictive embryology studies. Specifically, we demonstrate the capacity of RNA-seq as a promising tool in preimplantation screening by showing that biopsies of an embryo can capture valuable information content available in the whole embryo from which they are derived. Furthermore, we show that this technique can be used to generate a RNA-based digital karyotype, and to identify candidate competence-associated genes. Together, these data establish the foundation for a future RNA-based diagnostic in IVF.

  Dataset EGAD00001005044

• T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS)

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to type 2 diabetes in multiple ethnic groups using next generation sequencing. To fulfill this objective, T2D-GENES Consortium undertook two large sequencing studies, called T2D-GENES Projects 1 and 2. Project 1 has carried out whole exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 non-diabetic controls, equally divided among five continental ancestry groups: Europeans, East Asians, South Asians, Hispanic Americans, and African Americans. The goal of Project 1 is to identify all genetic variants in the complete coding regions of the genomes (i.e., whole exome) by sequencing, including rare variants. Project 2 (i.e., SAMAFS substudy 2) is a pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence information from approximately 600 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas, augmented with family-based imputation into approximately 440 additional family members. The major objectives of Project 2 are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. Both T2D-GENES Projects 1 and 2 involve the San Antonio Mexican American Family Studies (SAMAFS), which are composed of four San Antonio, Texas-based family studies: the San Antonio Family Heart Study (SAFHS), San Antonio Family Diabetes/Gallbladder Study (SAFDGS), Veterans Administration Genetic Epidemiology Study (VAGES), and Family Investigation of Nephropathy and Diabetes - San Antonio (FIND-SA) Component and its extension called the Extended FIND [E-FIND]. The SAFHS and SAFDGS began in 1991 and have followed participants with extensive clinical phenotyping related to T2D for over 20 years. The VAGES was initiated in 1994 and a large battery of T2D-related phenotypic data has been obtained from its participants. The FIND-SA began in 2000, a part of the multicenter FIND study which was designed to identify genetic determinants of diabetic kidney disease; data from its participants related to T2D were used for this project. Non-overlapping subsets of SAMAFS participants are part of the T2D-GENES Projects 1 and 2, henceforth referred to as SAMAFS substudies 1 and 2, respectively. The SAMAFS substudies 1 and 2 are part of one of the five awards funded by NIDDK under a cooperative agreement award mechanism, which is governed by the Steering Committee of the T2D-GENES Consortium. Since Project 1 relies on population based subsets of cases and controls, 491 unrelated participants are drawn from the four SAMAFS as part of the T2D-GENES Project 1 Mexican American sample (i.e., SAMAFS substudy 1). The whole exome sequencing was performed at the Broad Institute. For Project 2, 1048 individuals are drawn from two SAMAFS (SAFHS and SAFDGS), representing 20 large families for substudy 2. The substudy 2 strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The available sample of 1,048 includes 5 sequenced individuals who do not belong to any of the 20 large pedigrees. The final family data of 1,043 individuals includes whole genome sequence data for 607 individuals. After quality control, 590 sequenced individuals provide data for family based imputation using Merlin linkage analysis software into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. The complete SAMAFS data including phenotype, genotype, sequence, other T2D-related trait data utilized for Projects 1 and 2 are available. These data can readily be viewed by clicking on the substudy title shown below or in the box: "Substudies", located on the right hand side of this parent or top study page phs000847.v1.p1, titled T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS). phs000849 T2D-GENES Project 1: San Antonio Mexican American Family Studies (SAMAFS), Substudy 1: Whole Exome Sequencing phs000462 T2D-GENES Project 2: San Antonio Mexican American Family Studies (SAMAFS), Substudy 2: Whole Genome Sequencing in Pedigrees

  Study phs000847