1217 results for ""initial+cohort"+"mid-2020s"+"consortium"+"scholarly+exchange"+"university""

in 18.55 milliseconds.

• Whole-exome sequences of ovarian clear cell carcinomas and paired normal DNA

  Whole-exome sequencing dataset for the Australian Ovarian Cancer Study (AOCS) and The Jikei University School of Medicine (JIKEI) ovarian clear cell carcinoma (OCCC) clinical outliers project, representing 10 donors. Consists of 20 fastq files: one normal and one tumour from each patient.

  Dataset EGAD00001006004

• Dataset on keratinocytic gene expression pattern in Hidradenitis suppurativa

  Human skin samples were obtained from HS patients after informed consent (Ethical vote, University of Würzburg; No. 306/12). Lesional and perilesional were taken and epidermis and dermis separated. Isolated epidermal keratinocytes were further processed for RNA isolation. mRNA was extracted from five pairwise-matched lesional and perilesional epidermal HS pellets and RNA sequencing was performed.

  Dataset EGAD00001008005

• Colorectal cancer WES/WGS analysis in Dr. Liu’s group in Sun Yat-sen University Cancer Center

  The samples include paired tumor and normal tissues from 205 patients (201 for normal and primary tumor tissues; 4 for normal, primary tumor and liver metastatic tissues). High-coverage WES sequencing or whole genome sequencing of DNA samples were performed on the Illumina HiSeq 2000 system

  Dataset EGAD00001003452

• Brain Arteriovenous Malformation Genetics Study

  The Predictors of Spontaneous Cerebral AVM Hemorrhage study was designed to identify genetic markers that predict adverse outcomes in brain arteriovenous malformation (BAVM) patients, examine race-ethnicity influences on BAVM hemorrhage risk, and use genome-wide association analysis to identify novel genetic predictors of AVM and hemorrhage using the Affymetrix GeneChip. We performed the first genome-wide association study (GWAS) (PMID: 26818729) of sporadic BAVM to investigate association of common single nucleotide polymorphisms (SNPs) with risk of sporadic BAVM in the international, multicenter Genetics of Arteriovenous Malformation (GEN-AVM) consortium. The study included a Caucasian discovery cohort of 515 BAVM cases and 1,191 controls genotyped using Affymetrix genome-wide SNP arrays. The Phase 1 discovery cohort comprised of 338 BAVM cases (154 male) and 504 controls genotyped using the Affymetrix Genome-Wide Human SNP Array 6.0. The molecular data (individual genetic data) for the Phase 1 discovery cohort 338 BAVM cases (self-reported Caucasian) recruited at University of California, San Francisco, or Kaiser Permanente of Northern California (KPNC) are included in the dbGaP Study Report: Brain Arteriovenous Malformation Genetics Study, with the additional BAVM case phenotypic and sample attribute characteristics: sex, race, age at BAVM diagnosis, hemorrhagic presentation, BAVM size. Written informed consent was obtained from all participants and the study was approved by the respective Institutional Review Boards. The molecular dataset for this study in dbGaP is based on the genotypes obtained for the initial set of 906,600 SNPs for cases and controls called together using Birdseed v2 algorithm in Affymetrix Genotyping Console Software. The final QC'd dataset includes 717,335 markers as SNPs with MAF<0.01 or deviating from Hardy-Weinberg equilibrium (P<0.00001) in controls were excluded. After QC, the average genotyping call rate was 99%. The discovery phase GWAS identified 57 top BAVM-associated SNPs which were tested in a replication cohort including 608 BAVM cases and 744 controls. The molecular dataset for these 338 BAVM cases was also included in a report investigating common and rare genome-wide copy number variation for association with BAVM (PMID: 24098321), which included a total sample size of 371 sporadic Caucasian BAVM cases and 563 Caucasian controls. This study identified a CNV region on 1p36.13 (NBPF1 locus) that was significantly enriched with duplications in BAVM cases compared to controls, although this association did not replicate in an independent cohort of 184 sporadic BAVM cases and 182 controls. This resource will help researchers to better understand the genetic risk factors for BAVM and/or hemorrhage. These data may be applied to examine the genetic contributions to arteriovenous malformation, stroke, and related vascular disorders and may help generate hypotheses regarding the genetics of cerebrovascular disease.

  Study phs002069

• Providing safe access to sensitive human data across borders: Federated EGA becomes a reality

  Enabling discovery and access to sensitive data across national boundaries is vital for improving human health. It enables more powerful and efficient research by increasing the volume and diversity of data available for analysis. It allows us to better understand the causes of diseases – cancer, rare diseases, infectious diseases like COVID-19 – and develop new medicines and treatments. Sensitive human omics data are typically generated by research initiatives and shared using specialist repositories which provide services for data submission, discovery, and access. The EGA is one such repository. Established in 2008 at EMBL’s European Bioinformatics Institute (EMBL-EBI) in the UK, since 2012 the EGA (“Central EGA”) has been jointly managed by EMBL-EBI and the Centre for Genomic Regulation (CRG) in Spain. Many countries have emerging personalised medicine programmes which generate data from national initiatives. These programmes are driving a transition in human genomics from being research-driven to receiving funding through healthcare. Data generated in a clinical context are subject to stricter governance than research data and must follow national data protection legislation. To solve these challenges, the Federated EGA provides a network of connected resources to enable transnational discovery of and access to human omics data for research, while also respecting jurisdictional data protection regulations. In this way, the Federated EGA infrastructure supports the goals of European initiatives such as the 1+ Million Genomes initiative (1+MG), the European Health Data Space, and a number of EU-funded 1+MG implementation projects including Beyond 1 Million Genomes. The Federated EGA is made up of “Nodes” – typically nationally funded and operated – which store and manage data locally while allowing global discovery within the Federated EGA network. Since 2016, multiple parallel efforts, supported by ELIXIR and other transnational and national initiatives, have created technical and legal frameworks for establishing the Federated EGA. In 2022, the first five Nodes – Finland, Germany, Norway, Spain, and Sweden – officially joined the Federated EGA by signing Federated EGA Collaboration Agreements with Central EGA. The Finnish FEGA Node is operated by CSC - IT Center for Science and provides data management services according to national laws and the requirements of the EU General Data Protection Regulation (GDPR). These services provide tools and support for the whole life-cycle of sensitive research data from collating to analysis, publication, and authorised re-use. The development of the services has been a joint effort with the other Nordic nodes within NeIC's Tryggve and Heilsa projects, and funded by Finnish Ministry of Education and Culture and projects coordinated by ELIXIR Finland. Read more about Finnish FEGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. In Norway, a key component of the infrastructure is the services of The Sensitive Data Service (TSD) offered by USIT at University of Oslo. The Federated EGA Norway Node is developed by ELIXIR Norway and operated by the University of Oslo as the responsible legal entity. Core software modules are developed jointly with the other Nordic nodes in the NeIC Tryggve and Heilsa projects. Read more about FEGA Norway signing. The Spanish FEGA (es-FEGA) is a national service for storing sensitive biomedical data in Spain. Supported by the Spanish Institute of Bioinformatics (INB) in collaboration with Central EGA, sensitive research datasets are primarily hosted at the Barcelona Supercomputing Centre facilities. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. By providing a solution for secure and efficient management of human omics data, the Federated EGA aims to foster data reuse, enable reproducibility, accelerate biomedical research, and improve human health. Find out more Interested in setting up your own Federated EGA Node? Check out the FEGA Onboarding Knowledge Base for more information. The ELIXIR Federated Human Data Community is a great entry point for anyone interested in learning more about the Federated EGA. You can: Join the ELIXIR Federated Human Data Community mailing list (select “Human Data”) Attend the ELIXIR Federated Human Data Community calls

  Blog safe-access-to-sensitive-human-data-federated-ega

• InTEAM Consortium - Alcoholic Hepatitis

  Alcoholic hepatitis (AH) is a life-threatening condition characterized by profound hepatocellular dysfunction for which targeted treatments are urgently needed. Identification of molecular drivers is hampered by the lack of suitable animal models. By performing RNA sequencing in livers from patients with different phenotypes of alcohol-related liver disease (ALD), we describe the transcriptional programs involved in disease progression. We uncovered that development of AH is characterized by the defective activity of liver-enriched transcription factors (LETFs). The PPARG predicted activation state was found increased in early forms of ALD, while AH was associated by a marked decrease in HNF4A-dependent gene expression along with a marked expression of the fetal HNF4A isoform (P2). TGFB1, a key upstream transcriptome regulator in AH, induced the use of HNF4a P2 promoter in hepatocytes, which resulted in abnormal bile acid synthesis and defective metabolic and synthetic functions. PPARG agonists partially prevented this effect. We conclude that targeting TGFB1 and epigenetic drivers that modulate HNF4A-dependent gene expression could be beneficial to improve hepatocellular function in patients with AH. The study was conducted thanks to a multicenter collaboration under the National Institute of Alcohol Abuse and Alcoholism (NIAAA)-funded consortium: Integrated Approaches for Identifying Molecular Targets in Alcoholic Hepatitis (InTEAM).

  Study phs001807

• ADHD Genomic Association Study

  Studies at Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Netherlands, has recruited participants with ADHD and participants without ADHD, which included matched healthy controls and family members of participants with ADHD. ADHD participants met DSM-IV-TR criteria for ADHD. DNAs of these participants, 1005 samples, were anonymously genotyped with Illumina PsychArray. These samples were not part of the PGC-ADHD group. After removing family members, 820 case/control independent samples, including 211 ADHD cases, went through genomic association analyses. Results of ADHD risk genetic markers were compared with genetic markers associated with brain structure alterations in ADHD in adults and adolescents.

  Study phs001869

• Vitamin-D-Kids Asthma

  The Vitamin D Kids Asthma Study (VDKA) was a 48-week multicenter randomized, double-blinded, placebo-controlled trial of vitamin D3 for severe asthma exacerbations in children 6-16 years old, recruited from February 28, 2016 to September 20, 2019. An ancillary study for nasal sampling was conducted at the Pittsburgh site. Prior to randomization, participants completed questionnaires and underwent collection of nasal samples for gene expression studies. VDKA was approved by the IRBs of all participating institutions, and the ancillary study was approved by the IRB of the University of Pittsburgh. Written parental consent was obtained for participating children, from whom written assent was also obtained.

  Study phs004051

• MorphoITH: A Framework for Deconvolving Intra-Tumor Heterogeneity Using Tissue Morphology

  This study introduces MorphoITH, a framework for deconvolving intra-tumor heterogeneity (ITH) in clear cell renal cell carcinoma (ccRCC) based on tissue morphology from histopathological slides. The study tested MorphoITH's ability to capture different aspects of morphology and to reflect genetic ITH. The data deposited here is derived from a morphology guided multi-regional sequencing dataset used to study the relationship between morphology and genetic evolution. This dataset consists of whole exome sequencing of tumor from multiple sites and adjacent normal samples which were collected from two patients treated in affiliated hospitals of the University of Texas Southwestern Medical Center (UTSW), including Parkland Hospital.

  Study EGAS50000001064

• National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC)

  Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD.

  Study phs000571

• H3Africa Consortium WGS VCF

  Joint called VCF for whole genome sequence data from 410 samples described in the paper: PMID:33116287. It includes 314 high coverage (average 30X) samples sequenced on the Illumina X-Ten, also available as individual datasets under the H3Africa Chip study (EGAS00001002976) and 112 medium coverage (average 10X) samples from the TrypanGen study (EGAS00001002602) sequenced on Illumina HiSeq 2500. Supplementary table 3 of the paper describes the geographic breakdown of the samples. 16 samples from the Southern African Human Genome project have been removed from this VCF.

  Dataset EGAD00001008577

• Identification of low frequency variants associated with ulcerative colitis using whole-genome sequencing

  2000 ulcerative colitis cases drawn from the UKIBD Genetics Consortium cohort and whole-genome sequenced at 2X depth. A case control association study using control samples whole-genome sequenced by UK10K will be undertaken to identify common, low-frequency and rare variants associated with ulcerative colitis. Data will be combined with similar data across 3000 Crohn's disease cases from the same cohort to identify inflammatory bowel disease (IBD) loci and better understand the genetic differences and similarities of the two common forms of IBD.

  Dataset EGAD00001000409

• A Genome-Wide Association Study of Heroin Dependence

  This collaboration of Australian and American investigators aims to identify genes associated with liability for heroin dependence. The project uses a case-control design in which cases met lifetime DSM-IV criteria for heroin dependence. Controls included assessed individuals who did not meet DSM-IV heroin dependence criteria and unassessed general population controls. Cases and controls were obtained from the several large investigations including: The Comorbidity and Trauma Study, Heroin Dependence in Western Australia, the OZ-ALC Study, a Twin Study of Mole Development in Adolescence, and ongoing genetic studies of substance dependence conducted by investigators at Yale and collaborating institutions. These projects are briefly described below. The Comorbidity and Trauma Study (PI: Elliot Nelson), a retrospective case-control study examining genetic and environmental factors contributing to heroin dependence liability. The study was funded by the National Institute on Drug Abuse (NIDA), and was run in collaboration with Washington University, the Queensland Institute of Medical Research (QIMR), and the National Drug and Alcohol Research Centre (NDARC), University of New South Wales. Case participants were recruited from maintenance clinics in the greater Sydney area. Control participants were recruited from employment centres and community centres, open street malls, and local press servicing the same geographical area as the opioid maintenance treatment clinics and either denied recreational use of opioids or had used these drugs recreationally fewer than 11 times lifetime. The prevalence in these individuals of non-opioid licit drug dependence and illicit drug dependence as well as childhood trauma exposure and other psychiatric disorders is elevated considerably versus estimates of similar measures in Australian general population samples. Participants provided blood samples as a source of DNA and completed a comprehensive psychiatric diagnostic interview based on the Semi-Structured Assessment of the Genetics of Alcoholism - Australia (SSAGA-OZ) augmented with sections drawn from other instruments assessing childhood trauma exposure, family history, and screening for borderline personality disorder. Heroin Dependence in Western Australia (PI: Sybille Schwab) is a study focusing both on genetic contributions to heroin dependence and response to naltrexone treatment of the disorder. Participants completed a clinical assessment and provided blood samples during their treatment at the Perth Naltrexone Clinic now name as the Fresh Start Recovery Programme. Funding for the project was provided by the Australia Government's National Health and Medical Research Council (Grant # 513862; PI: Sybille Schwab) Affected subjects from ongoing genetic studies of substance dependence conducted by investigators at Yale (PI: Joel Gelernter) and collaborating institutions were collected in the course of several NIDA-funded studies. Those included in the current set were assessed by means of the SSADDA (Semi-Structured Assessment for Drug Dependence and Alcoholism). All are opioid dependent European-Americans, and all list heroin as the opioid must used. Most were collected at Yale University School of Medicine or University of CT School of Medicine under the supervision of Drs Joel Gelernter and Henry Kranzler. Control subjects were also collected in the course of several NIDA- and NIAAA-funded studies. Those included in the current set were assessed by means of the SSADDA (Semi-structured Assessment for Drug Dependence and Alcoholism). Most were collected at Yale University School of Medicine or University of Connecticut School of Medicine under the supervision of Drs Joel Gelernter and Henry Kranzler. The OZ-ALC Study (PI: Andrew Heath) consists of a large group of twins and their family members ascertained from the general population Australian Twin Registry who have participated in ongoing research projects. For the control investigation, we have selected individuals who do meet criteria for illicit drug dependence who have had GWAS genotyping with the Illumina Human CNV370-Quad. Inclusion of individuals with alcohol dependence or nicotine dependence was minimized. For a more detailed description of the study, please see: http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000181.v1.p1 The Twin Study of Mole Development in Adolescence (PI: Nick Martin) is an ongoing investigation of melanocytic naevi funded by the Australian Government's National Health and Medical Research Council (Grant # 389891; PI: Nick Martin). For the current project, unassessed parents of these twins will serve as a control group. These individuals will either have been previously genotyped with the Illumina Human 610-Quad BeadChip or will be genotyped as part of the current project. Parents have largely survived the period of risk for heroin dependence and, by virtue of their participation in this research, are very likely to have a prevalence of heroin dependence lower than that in the general population (i.e., <0.7%). In order to understand the immune modulatory effect of opioids across peripheral blood immune populations, a second study (PI: Christine S. Cheng) analyzed single cell RNA-seq profiles from the PBMCs of a subset of case participants and control participants from the Comorbidity and Trauma Study (PI: Elliot Nelson). The study assessed and identified transcriptional changes between opioid dependent and control samples across naive and LPS stimulated immune populations.

  Study phs000277

• Newcastle COVID-19 Single-cell PBMC

  Single-cell multi-omic profiling of healthy controls, asymptomatic and hosptial-admitted COVID19 patients recruited from Newcastle University hospitals. These data also include healthy control volunteers treated with IV-LPS as inflammatory controls. Data represent RNA-seq, surface protein measurements (CITE-seq) of 192 antibody targets, along with VDJ-seq profiling of single T cell and B cell receptors.

  Dataset EGAD00001007866

• The Chinese University of Hong Kong Hereditary Spastic Paraplegia Data

  The dataset contains the whole genome sequencing data of a family with two unaffected parents and two probands that showed Hereditary spastic paraplegias symptoms. Sequencing reads were aligned to human genome (GRCh38) using BWA-MEM, followed by indel-realignment and PCR-duplicates marking. Alignment results are available for download in BAM format.

  Dataset EGAD00001002146

• Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomic Confirmatory Study of Breast, Colon, Lung, and Ovarian Tumors

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.). The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein-protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the second phase of the CPTC initiative in September 2011. Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples. These confirmatory samples contain breast, ovarian, colon, and lung tumors collected via a protocol optimized for proteomics. Specifically, ischemic time of the sample was controlled and restricted to less than 30 minutes. ACGT, Inc. produced whole exome, mRNAseq, and miRNAseq for these samples. Corresponding proteomic data are available at: https://cptac-data-portal.georgetown.edu/cptacPublic/ The study design was to profile colon, breast, ovarian, and lung tumors both genomically and proteomically. Germline DNA was obtained from blood. Normal control samples for proteomics varied by organ site: adjacent colon tissue for colon cases, contralateral breast tissue for some breast cases, and Fallopian tube fimbria for some ovarian cases. Lung cases had no normal control for proteomic analysis. All cancer samples were derived from primary and untreated tumors.

  Study phs000892

• Genetic Basis of Early Onset Bicuspid Aortic Valve Disease

  The study protocol was approved by the Committee for the Protection of Human Subjects at the University of Texas Health Science Center at Houston (HSC-MS-11-0185). Study recruitment began on July 1, 2017, and concluded on March 30, 2022. After written informed consent, we enrolled probands with early onset BAV disease (EBAV), which we defined as individuals with BAV who were under the age of 30 at the time of first clinical event. Clinical events were defined as aortic replacement, aortic valve surgery, aortic dissection, moderate or severe aortic stenosis or aortic regurgitation, large aneurysm (Z > 4.5), or intervention for BAV-related conditions. Those with hypoplastic left heart, known genetic mutations, genetic syndromes, or complex congenital heart disease were excluded. Samples were collected and genotyped as previously reported. For comparison, we analyzed a cohort of older individuals of European ancestry with sporadic BAV disease selected from the International BAV Consortium (BAVGWAS). Phenotypes were derived from record review with confirmation of image data whenever possible [25-26]. The computational pipeline for CNV analysis of Illumina single nucleotide polymorphism (SNP) array data included three independent CNV detection algorithms.GenomeStudio was used to exclude samples with indeterminate sex or more than 5% missing genotypes, and single nucleotide polymorphisms (SNPs) with GenTrain = 0. Principal component analysis was used to remove outliers that did not cluster with European ancestry. Prior to CNV analysis, each dataset was trimmed by selecting a common set of 650,000 SNPs that were genotyped on each of the microarrays used in this study.Three independent algorithms (PennCNV, cnvPartition, and QuantiSNP) were used to generate CNV calls and sample-level quality statistics from SNP intensity data. PennCNV and QuantiSNP were run on Unix clusters and cnvPartition data were exported from GenomeStudio. The analysis was run using default configurations. PennCNV was used to generate QC data and remove CNV calls that intersect with polymorphic genomic regions. Samples that met any of the following criteria were excluded, standard deviation of the LogR ratio (obtained from PennCNV) > 0.35 or number of CNVs > 2 standard deviations above the mean for each data set. CNV calls less than 20 Kilobases in length and/or spanned by fewer than 6 probes were excluded. The overlap function for rare CNVs in PLINK was used to construct CNV regions (CNVRs) after adjacent regions were merged using PennCNV. LogR ratio (LRR) and B allele frequency (BAF) data at CNVRs and calls of interest were visualized in GenomeStudio for validation. For segregation analysis, GenomeStudio was used to determine the presence of CNVs in relatives.A total of 22,014 unselected control Illumina Genotypes obtained from the Database of Genotypes and Phenotypes were analyzed using identical methods (S1 Table). The Wisconsin Longitudinal Study (WLS) includes data on a cohort of 10,300 individuals who graduated from Wisconsin high schools in 1957. The Health and Retirement Study (HRS) includes data on 37,000 individuals aged 50 above from 23,000 households across the United States. Principal component analysis was used to select European ancestry genotypes from these datasets for analysis. Datasets were paired for case-control analysis based on the concordance of log-transformed sample-level quality control statistics (number of CNV calls and standard deviation of logR ratios). Chi-squared or Fisher exact tests were used to compare CNV frequencies in cases and controls.Rare CNV functions in PLINK (v1.7) were used to perform permutation-based burden tests or gene set-based enrichment tests. Case control burden tests were restricted to CNVs that were longer than 110 Kb and less than 0.1% in frequency. CNV overlap functions in PLINK were used to identify rare CNVs that intersect between datasets or involve specific BAV or CHD genes . The list of candidate genes included 190 CHD genes that have strong cumulative evidence to cause BAV or related congenital malformations from human or animal model data. Genome Reference Consortium Human Build 37 was used for CNV annotation [34].

  Study phs003705

• Human Lung Tissue eQTL Study

  Genetic risks underlying respiratory diseases (e.g. COPD and asthma) are carefully studied by large genome-wide association studies (GWAS), where many loci were identified. In the post-GWAS era, the main challenge is to find the causal genes and pathways in GWAS-nominated chromosomal regions and to characterize etiology mechanism. The Lung eQTL Consortium is an international effort to systematically capture the genetic architecture of gene expression regulation in human lung. By studying lung specimens from 1,103 individuals of mostly European ancestry, we report a large number of genetic variants affecting gene expression in the lung, or lung expression quantitative trait loci (eQTL). These lung eQTLs will serve as an important resource to aid in the understanding of the molecular underpinnings of lung biology and its disruption in disease.

  Study phs001745

• Genetic Epidemiology of Chronic Lymphocytic Leukemia

  Chronic lymphocytic leukemia (CLL) is a subtype of B-cell lymphoproliferative disorders (LPD), and is the most common form of adult leukemia in Caucasians in the United States. Small lymphocytic lymphoma (SLL) is also a B-cell LPD and is typically considered to be the same disease as CLL, based on pathology. We consider CLL and SLL as the same disease entity, and hereafter refer to both simply as "CLL". Using genealogical databases and cancer records, the familial clustering for CLL is one of the strongest for all cancer sites, strongly implicating germline genetic risk. We ascertained CLL cases and controls for a genomewide association study (GWAS) that was undertaken as part of the International Lymphoma Epidemiology (InterLymph) consortium GWAS. Some CLL cases are also part of extended high-risk CLLpedigrees.

  Study phs001568

• AACR Project Genomics, Evidence, Neoplasia, Information, Exchange (GENIE)

  AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) is an international pancancer registry of real-world data assembled through data sharing between 19 leading international cancer centers with the goal of improving clinical decision-making. The registry leverages ongoing clinical sequencing efforts (CLIA/ISO-certified) at participating cancer centers by pooling their data to create a novel, open-access registry to serve as an evidence base for the entire cancer community. Genomic and baseline clinical data from more than 70,000 tumors is accessible through the efforts of our strategic and technical partners, Sage Bionetworks and cBioPortal. The consortium and its activities are driven by openness, transparency, and inclusion to ensure that the project output remains accessible to the global cancer research community and ultimately benefits patients.

  Study phs001337

• ICGC Oesophageal adenocarcinoma - tumour samples

  The oesophageal project will focus on adenocarcinoma which is increasing in incidence in the UK and other developed countries and has a very poor outcome. The primary aims of this project are to deeply sequence tumour and normal genomic DNA (including the precursor condition Barrett’s oesophagus when material is available) to provide a comprehensive catalogue of somatic mutations. This will be achieved through a UK-wide network of hospitals involved in a research collaboration called the OCCAMS consortium. The goal of this project is to use high quality clinical material with accurately annotated clinic-pathological, treatment and outcome data.

  Study EGAS00001000725

• WGS of liver cancer in the Japanese population

  Hepatocellular carcinoma (HCC) is the third leading cancer-related cause of death and the seventh most common form of cancer worldwide, with an estimate of more than 700,000 new cases each year. The most established risk factors of HCC are chronic HBV and HCV infection. HBV infection is responsible for over 50% of the worldwide attributable risk of HCC, especially in East Asia and Africa, while in Japan and several Western countries HCV infection is the most common risk factor for HCC. To gain insights into the molecular alterations of virus-associated HCC, we performed whole genome sequencing (WGS) of 321 HCC tumors from 159 patients. This work was performed as a part of the ICGC (International Cancer Genome Consortium) project.

  Study EGAS00001000678

• Synthetic data - Genome in a Bottle

  In May, the National Institute of Standards and Technology (NIST) released its first genome in a bottle, a reference sample of DNA for validating human genome sequences. This so-called truth sequence comes from a decades-old sample donated by a Utah woman for (other) research purposes (NA12878 cell line), which, over the years, has been one of the most studied, and hence best-characterized, human samples. Seeing genomic medicine moving toward mainstream healthcare, researchers at NIST recognized the need for a reference human genome and assembled a private-public consortium in 2012 to create one. As detailed in a 2014 Nature Biotechnology paper (Nat. Biotechnol.32, 246–251, 2014), the group integrated and arbitrated among sequences from 14 data sets, five sequencing technologies, seven read mappers and three variant callers.

  Study EGAS00001005591

• SNP array data for the Milieu Intérieur cohort

  The Milieu Intérieur Consortium aims at identifying the environmental and genetic factors driving variation in innate and adaptive immune systems among healthy individuals. In the last four years, we combined standardized flow cytometric analysis of blood leukocytes, transcriptional profiles of whole blood after immune stimulation and genome-wide DNA genotyping in 1,000 healthy, unrelated donors of western European ancestry, to show that age, sex, as well as persistent infections and smoking, are the most important drivers of inter-individual differences in blood cell composition and transcriptional response to pathogens. The EGAS00001002460 study includes genotype data for 5,699,237 genotyped and imputed SNPs in the 816 healthy donors of the Milieu Intérieur cohort. Note that 184 of the 1,000 initial donors did not agree to share their data online.

  Study EGAS00001002460

• Transdisciplinary Research Into Cancer of the Lung (TRICL) - Exome Plus Targeted Sequencing

  The study was conducted under the auspices of the Transdisciplinary Research In Cancer of the Lung (TRICL) Research Team, which is a part of the Genetic Associations and MEchanisms in ONcology (GAME-ON) consortium, and associated with the International Lung Cancer Consortium (ILCCO). Ethics All participants provided written informed consent. All studies were reviewed and approved by institutional ethics review committees at the involved institutions. Sequencing data are derived from four sub-studies. The sub-studies that contributed include Harvard, Liverpool, Toronto, and IARC. The IARC and Toronto studies are described above. A description of the Harvard and Liverpool studies is provided below. Liverpool Lung Project: The Liverpool Lung Project (LLP)1 is a case control and cohort study, which has over 11,500 individuals, with detailed epidemiological, clinical and outcome data with associated specimens (i.e. tumour tissue, blood, plasma, sputum, bronchial lavage, EBUS and oral brushings). The participants have completed a detailed lifestyle questionnaire and updated data on clinical outcome and hospital events are collected through the Office of National Statistics, Cancer Registry and from Health Episode Statistics. The project is registered on the UK National Institute for Health Research (NIHR) lung cancer portfolio and has all the required ethical approvals and sponsorship arrangements in place. The LLP has detailed standard operating procedures (SOP) for all aspects of the recruitment, data, specimen collection as well as the data storage. The LLP Cohort study has 8,224 participants with blood and 7,761 with plasma samples. The LLP case-control samples have been incorporated into in a large number of international GWAS and molecular studies 2,3, methylation 4-7, microRNA 8and next generation studies 9-11, resulting in high ranking publications, as well as forming the basis for the LLP risk prediction model 12-14 which has been utilised in the UK lung cancer screening trial (UKLS) 15-17 Patient and control DNAs were derived from EDTA-venous blood samples. Harvard Samples. David Christiani at the Harvard University School of Public Health has been directing research studies to investigate etiological factors influencing lung cancer development since 1983 and has amassed a collection of 2000 controls and 5055 lung cancer cases. He has been actively collecting and storing snap frozen tumor samples since 1992. Around 1500 tumor samples have been collected and the average wet tumor yield is about 30 grams of tumor, of which 631 cases have completely annotated clinical and survival information. Pathology confirmation is provided by two pathologists. At the time of surgery, a minimum of 30 grams of wet lung tumor tissue and 30 grams of non-involved tissue from the same lobe is sectioned, flash frozen and sent to Dr. Christiani's lab for logging and storage. A blood sample for DNA and serum is collected. A structured interview by trained research staff is conducted on each case, and clinical outcomes and treatments is extracted and entered into the molecular epidemiology data base at Harvard. Fresh frozen samples have been collected from 1451 lung cancer and are available for study. Samples from this collaborative study have played key roles in major studies, including the initial finding describing EGFR mutations in lung cancer 22. Participants in this study are patients, > 18 years of age, with newly diagnosed histologically confirmed lung cancer. Samples that are included in the analysis have the following histologies: Adenocarcinoma: 8140/3, 8250/3, 8260/3, 8310/3, 8480/3 8560/3; LCC: 8012/3, 8031/3; squamous carcinoma: 8070/3, 8071/3, 8072/3, 8074/3; and other NSCLC: 8010/3, 8020/3, 8021/3, 8032/3, 8230/3. The Toronto Study: The Toronto study was conducted in the Great Toronto Area between 1997 and 2014. Cases were recruited at the hospitals in the network of University of Toronto and Lunenfeld- Tanenbaum Research Institute. At the time of recruitment in the clinical setting, provisional diagnoses of lung carcinoma were first assigned based on clinical criteria. Diagnoses for all cases included were histologically confirmed by the reference pathologist who is a specialist in pulmonary pathology, based on review of pathology reports from surgery, biopsy or cytology samples in 100% of cases. Diagnostic classification was done initially according to ICD-9, ICD-10, and ICD for oncology-2, and subsequently converted to ICD-O-3. Tumors were grouped into the major categories included in this analysis according to primary cancer type based on the ICD-3 definitions. Controls were randomly selected from individual visiting family medicine clinics and Ministry of Finance Municipal Tax Tapes. All subjects were interviewed using a standard questionnaire and information on lifestyle risk factors, occupational history, medical and family history was collected. Blood samples were collected from more than 85% of the subjects. IARC: The IARC data are derived from case-control studies conducted in Russia and include samples that have available tissue samples. Patient and control DNAs were derived from EDTA-venous blood samples. The lung cancer patients were classified according to ICD-O-3; SQ: 8070/3, 8071/3, 8072/3, 8074/3; AD: 8140/3, 8250/3, 8260/3, 8310/3, 8480/3, 8560/3, 8251/3, 8490/3, 8570/3, 8574/3; with tumous with overlapping histologies classified as mixed. The Lung Cancer Transdisciplinary Research Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs000876 Lung Cancer Transdisciplinary Research Cohort. phs000877 Meta Analysis phs000878 CIDR Lung Cancer phs001681 Affy Axiom Array

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