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• Hostage_3_genotype

  Cohort: Raw genotype files for Hostage3 cohort. Genotype Chip: Illumina’s (Illumina Inc., San Diego, U.S.) Global Screening Array-24 Multi Disease (GSA) Version 2.0 B1 genomic build: b37

  Dataset EGAD00010002173

• Hostage_2_genotype

  Cohort: Raw genotype files for Hostage2 cohort. Genotype Chip: Illumina’s (Illumina Inc., San Diego, U.S.) Global Screening Array-24 Multi Disease (GSA) Version 2.0 B1 genomic build: b37

  Dataset EGAD00010002171

• Myocardial Infarction Genetics Exome Sequencing Consortium: University of Lubeck

  MI cases were recruited from the German MI Family Study and the Angio-Lub study. Controls were recruited from the German MI Family Study and the Angio-Lub study. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Illumina's ICE Capture reagent and sequencing was performed on an Illumina HiSeq 2000 or 2500.

  Study phs000990

• Genomic sequencing of Ewing's Sarcoma

  The Ewing sarcoma family of tumors (EFT) is a group of malignant small round blue cell tumors that arise in bone or soft tissue. Ewing sarcoma (ES) is the second most common type of primary bone tumor to affect children and adolescents and accounts for 2.9% of all childhood cancers. This data set reports whole-genome sequencing of 6 primary Ewing's Sarcoma samples and matching germline samples.

  Study phs000768

• cfMeDIP-seq for 18 patients with pleural mesothelioma

  The dataset contains cfMeDIP-sequencing data (bam files) for 18 plasma samples from pleural mesothelioma patients. The libraries were prepared according to the published protocol (Shen, S. Y., Burgener, J. M., Bratman, S. V. & De Carvalho, D. D. Preparation of cfMeDIP- seq libraries for methylome profiling of plasma cell-free DNA. Nat. Protoc. 14, 2749–2780 (2019)). Whole genome sequencing (WGS) was performed for pre-made libraries on NovaSeq X Plus with a 150 paired-end strategy. Low-quality reads and adapters were removed with Trim Galore version 0.6.6 (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore). The trimmed reads were aligned to hg38 with Bowtie2 version 2.3.4.3. SAMTools version 1.9 was used to convert the SAM alignment files to BAM files, sort and index reads, and remove duplicates.

  Dataset EGAD50000002126

• The National Institute of Neurological Disorders and Stroke (NINDS) Stroke Genetics Network (SiGN)

  The NINDS Stroke Genetics Network (SiGN) is a large international collaboration designed to detect genetic variants that predispose to subtypes of ischemic stroke. The study implements a genome wide association study (GWAS) methodology with all stroke cases undergoing phenotypic and stroke-subtype classification using the same web-based Causative Classification of Stroke (CCS) system, with data entered by trained and certified adjudicators at participating Research Centers (GRC's). SiGN includes ischemic stroke cases from 24 GRC's, 13 from the US and 11 from Europe. Each GRC has access to well-characterized ischemic stroke cases in which extensive phenotype data and high-quality DNA was available. Genome-wide data was available for many cases and for those without, new genome-wide genotyping, including exome chip genotyping of rare variants, was done through the Center for Inherited Diseases Research (CIDR). To maximize power for subtype analyses, genotyping resources were allocated almost exclusively to cases. With few exceptions, controls were drawn from studies with publicly available genome-wide data.

  Study phs000615

• Barrett's and Esophageal Adenocarcinoma Genetic Susceptibility Study (BEAGESS)

  BEAGESS is a genome-wide association study (GWAS) which takes advantage of the extensive data collected by investigators in the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON, http://beacon.tlvnet.net), representing many of the high-quality population-based and other epidemiologic studies of BE and EA in the world. The overall goal of our research is to evaluate the influence of genetic susceptibility on risk of EA and its main precancerous condition, BE. The primary aims of the study are to identify tagSNPs most strongly associated with risk of esophageal adenocarcinoma (EA) and Barrett's esophagus (BE). In the secondary aims we will evaluate the extent to which the most significant associations vary according to key environmental and host factors for these conditions, including gender, obesity and cigarette smoking. These results will guide additional exploratory analyses examining ways in which individual SNP results might be aggregated to shed light in the importance of specific pathways relevant to the etiology of BE and EA, and to identify possible epistatic effects.

  Study phs000869

• Functionally Active Copy Number Variants Associated with Prostate Cancer Risk

  Prostate cancer is a leading cause of cancer death in males throughout the world and has the largest estimated effect of heritability among the most common tumor types. Copy Number Variants (CNVs) are a recently recognized class of human germline polymorphisms (Iafrate AJ, et al. (2004) Nat Genet 36, 949-951; Sebat J, et al. (2004) Science 305, 525-528.) and are associated with a variety of human diseases, including cancer. This study characterized 1,903 individuals from the Tyrol Early Prostate Cancer Detection Program (Bartsch G, et al. (2008) BJU Int 101, 809-816) using a computational framework (Banerjee S, et al. (2011) PLoS One 29;6(3)). The study results establish non-coding and coding germline CNVs as significant risk factors for prostate cancer susceptibility and implicate their role in disease development and progression. The study "Identification of functionally active, low frequency copy number variants at 15q21.3 and 12q21.31 associated with prostate cancer risk," Demichelis F, Setlur SR, Proc Natl Acad Sci U S A. 2012 Apr 24;109(17):6686-91.

  Study phs000487

• WGS of T-cell and NK-cell lymphoma for ICGC (NKTL-SG)

  Lymphomas are malignancies originating from the lymphatic system and there is a worldwide significant increase in incidences of this cancer. Lymphomas can be further classified into 2 categories namely Hodgkin’s (HL), and Non-Hodgkin’s lymphoma (NHL). The latter can be divided further into B, T and NK cell NHL. Peripheral T-cell lymphoma (PTCL) and Natural Killer/ T-cell lymphoma (NKTL) arise from mature T lymphocytes and NK cells. The more common subtypes include NKTL, PTCL not-otherwise-specified (PTCL-NOS), systemic anaplastic large cell lymphoma (ALCL), follicular PTCL (F-PTCL), angioimmunoblastic T-cell lymphoma (AITL) and enteropathy-associated T-cell lymphoma (EATL). Whole genome analyses on T-cell and NK-cell lymphoma samples from various countries to gain a better understanding of the pathogenesis and biology of these tumors. The comprehensive profiling and comparison among patients from various countries with different etiopathogenesis will hopefully facilitate the elucidation of key pathways and underlying molecular mechanisms driving these cancers, opening up novel therapeutic strategies in the future.

  Study EGAS00001002398

• Profiling Genome-Wide Circulating ncRNAs for the Early Detection of Lung Cancer

  Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of all cases. Although imaging techniques such as low-dose computed tomography (LDCT), combined with tissue biopsies, have improved early detection rates, current diagnostic approaches are often limited by high false-positive rates, invasiveness, and radiation exposure, which lead to misdiagnosis and increased patient burden. Therefore, there is an urgent need for minimally invasive, accurate, and safe diagnostic biomarkers, particularly those derived from liquid biopsies such as blood-based exosomal RNA.This dataset specifically focuses on plasma-derived exosomal small non-coding RNAs (sncRNAs).A total of 233 de-identified plasma samples were obtained from Rush University Medical Center, including 116 NSCLC patients and 117 non-cancer controls. Exosomes were isolated from plasma, RNA was extracted, and small RNA sequencing was performed using the Illumina NextSeq 500 platform. Data available through dbGaP include individual-level raw sequencing files (FASTQ) and basic phenotype annotations of the plasma cohort.A diagnostic model was initially developed using small RNA-seq data from 1,446 tissue samples obtained from TCGA and GEO, identifying a robust sncRNA signature that distinguished NSCLC from non-cancer samples with an AUC of 0.90 in hold-out tissue validation. This signature was subsequently validated in the plasma exosome cohort, achieving an AUC of 0.84 in independent validation. The model demonstrated consistent diagnostic performance across subgroups stratified by age, sex, smoking history, cancer stage, and NSCLC subtype. Survival and functional analyses further supported the clinical and biological relevance of the identified sncRNAs. It is hoped that this resource will contribute to a better understanding of the sncRNA expression landscape in NSCLC and promote the development of non-invasive biomarkers for early cancer detection. These data may be applied to the investigation of transcriptomic and other risk factors, provide insight into cancer screening, tumor progression mechanisms, and prognosis prediction, and ultimately support precision medicine for NSCLC.

  Study phs004166