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• RCi004-B / SAMEA3106205 WGS data

  The iPSC line RCi004-B / SAMEA3106205 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line RCi004-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001070

• RCi004-A / SAMEA3106011 WGS data

  The iPSC line RCi004-A / SAMEA3106011 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line RCi004-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001069

• UKKi018-C / SAMEA103988380 WGS data

  The iPSC line UKKi018-C / SAMEA103988380 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UKKi018-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001067

• EDi015-B / SAMEA4459375 WGS data

  The iPSC line EDi015-B / SAMEA4459375 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi015-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001066

• EDi013-C / SAMEA4459368 WGS data

  The iPSC line EDi013-C / SAMEA4459368 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi013-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001065

• EDi012-C / SAMEA4459364 WGS data

  The iPSC line EDi012-C / SAMEA4459364 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi012-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001064

• EDi012-B / SAMEA4459363 WGS data

  The iPSC line EDi012-B / SAMEA4459363 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi012-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001063

• UKKi017-C / SAMEA17621668 WGS data

  The iPSC line UKKi017-C / SAMEA17621668 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UKKi017-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001061

• EDi013-A / SAMEA4459365 WGS data

  The iPSC line EDi013-A / SAMEA4459365 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi013-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001057

• EDi010-B / SAMEA4459356 WGS data

  The iPSC line EDi010-B / SAMEA4459356 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi010-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001056

• RBi001-A / SAMEA3368212 WGS data

  The iPSC line RBi001-A / SAMEA3368212 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line RBi001-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001058

• RCi006-A / SAMEA3962402 WGS data

  The iPSC line RCi006-A / SAMEA3962402 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line RCi006-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001059

• BIONi010-B / SAMEA3158000 WGS data

  The iPSC line BIONi010-B / SAMEA3158000 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001055

• InterPregGen-GWAS-UZB-2

  GWAS genotype data for maternal and fetal (baby) cases of preeclampsia and controls from Uzbekistan. This dataset is a component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium members in Tashkent, Uzbekistan at the Institute of Immunology, Uzbek Academy of Sciences and at the Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology

  Dataset EGAD00010001917

• InterPregGen-GWAS-UZB-3

  GWAS genotype data for maternal and fetal (baby) cases of preeclampsia and controls from Uzbekistan. This dataset is a component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium members in Tashkent, Uzbekistan at the Institute of Immunology, Uzbek Academy of Sciences and at the Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology

  Dataset EGAD00010001919

• aCGH CNV detection by CNsolidate for 6,827 DDD probands

  aCGH CNV detection by CNsolidate for 6,827 DDD probands

  Dataset EGAD00001005728

• The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Genetics of Genetic Epidemiology of Metabolic Syndrome in an Island Population

  The major objective of this study was to conduct a systematic genetic study of metabolic traits involved in metabolic syndrome through collection and analysis of epidemiological, demographic, environmental, and relevant biological and clinical data from a relatively isolated island population of the eastern Adriatic coast of Croatia. The population was chosen for the following reasons: 1) in spite of practicing a largely traditional life style and dietary habits, high rates of obesity, arterial hypertension, dyslipidemia and related metabolic abnormalities were found in previous studies; 2) the population was established by a relatively small number of founders, predominantly of Slavic descent from the mainland during 15th to 18th century AD, a genetically homogeneous population living in a homogeneous environment; 3) sharing a common European ancestry, a relevant population for study in the context of the general US population; 4) Croatian collaborators have been conducting anthropological and genetic studies in these communities for over three decades. There were two major aims of the study: 1) to recruit ~1200 adult participants and collect blood samples together with demographic, anthropometric, environmental and clinical data from the island of Hvar; to perform biochemical tests to measure glucose, insulin, uric acid and lipid levels; 2) conduct a genome-wide association analysis of metabolic traits and phenotypes using genome-wide SNP arrays (Affymetrix Genome-Wide Human SNP Array 5.0).

  Study phs000737

• MPM cell lines

  RNA-sequencing data for 12 MPM cell lines treated with 0.1% DMSO or 1 µM palbociclib for 9-10 days. Experiment was performed in duplicates for sensitive cells (MPM08, MPM21, MPM38, MPM57, MPM59, Meso11, Meso13, Meso34 and Meso56) and only once for resistant cells (MPM31, MPM34 and MPM36) except for Meso11 which was done in triplicates. For Meso11, Meso13, Meso34 and Meso56, a drug washout of 48 hours was also performed. 4 MPM cell lines (MPM31, MPM34, MPM59 and MPM66) were also analyzed in untreated condition. 2 FASTQ files for each sample (n=56) (paired)

  Dataset EGAD00001008741

• SGCC GASCAD-II dataset

  The GASCAD-II dataset from the Singapore Gastric Cancer Consortium includes paired tumor-blood whole exome sequencing data for 209 gastric cancer (GC) patients, along with whole transcriptome sequencing data for 125 GC samples. Whole exome sequencing was conducted using Agilent SureSelect Human All Exon V6 kits. For RNA sequencing, total RNA was isolated using the RNeasy Mini Kit, and libraries were prepared with the TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina). Aligned BAM files for both exome and RNAseq data are included in this dataset

  Dataset EGAD00001015433

• Dataset for manuscript titled: Spatial Intra-Tumour Heterogeneity and Treatment-Induced Genomic Evolution in Oesophageal Adenocarcinoma: Implications for Prognosis and Therapy

  Dataset for manuscript titled: Spatial Intra-Tumour Heterogeneity and Treatment-Induced Genomic Evolution in Oesophageal Adenocarcinoma: Implications for Prognosis and Therapy

  Dataset EGAD00001015373

• PROGRESS/ELEMENT DNA Methylation Study

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

  Study phs002754

• NCI Expanded Genome-Wide Association Study of Renal Cell Carcinoma

  The National Cancer Institute (NCI) expanded genome-wide association study (GWAS) of renal cell carcinoma (RCC) was a 2nd GWAS of this cancer performed by NCI to further investigate common genetic variants associated with RCC risk. The GWAS includes 2,781 cases and 2,940 controls of European background from 13 studies conducted in the US and Finland (10 cohorts, 2 case series, 1 hospital biorepository), scanned using the Illumina OmniExpress and Omni2.5 SNP arrays. SNP-level results from this GWAS were combined by meta-analysis with results from the earlier NCI RCC GWAS (phs000351.v1.p1; 1,311 cases and 3,424 controls) and others conducted by the International Agency for Research on Cancer (scan 1: 2,438 cases and 5,071 controls; scan 2: 2,781 cases and 2,940 controls), The University of Texas MD Anderson Cancer Center (893 cases and 556 controls) and the Institute for Cancer Research, UK (944 cases and 4,024 controls). Only data from the second NCI scan are included in this dbGaP submission. Data from 239 cases and 229 controls from this scan will be deposited in dbGaP separately under the Women's Health Initiative (phs000200).

  Study phs001736

• banfora_20150706_X

  Genotype data (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 355 individuals from the VAC050 trial performed in Banfora, Burkina Faso - X chromosome.

  Dataset EGAD00010002579

• johannesburg_20150706_autosomes

  Genotype data and (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 750 individuals from Respiratory and Meningeal Pathogens Unit in Soweto, South Africa - autosomes.

  Dataset EGAD00010002582

• 4C-seq data

  4C-seq data was generated for regions of interest to confirm enhancer-gene promoter interactions

  Dataset EGAD00001001847

• SNV vcf files for CPCG Subclonal Heterogeneity

  SNV calls generated using the MuTect-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study

  Dataset EGAD00001004400

• SNV vcf files for CPCG Subclonal Heterogeneity

  SNV calls generated using the MuTect-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study

  Dataset EGAD00001004401

• SNV vcf files for CPCG Subclonal Heterogeneity

  SNV calls generated using the SomaticSniper-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study

  Dataset EGAD00001004402

• CNA vcf files for CPCG Subclonal Heterogeneity

  CNA calls generated using the MuTect-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study

  Dataset EGAD00001004403

• CNA vcf files for CPCG Subclonal Heterogeneity

  CNA calls generated using the MuTect-TITAN-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study

  Dataset EGAD00001004404

• CNA vcf files for CPCG Subclonal Heterogeneity

  CNA calls generated using the SomaticSniper-Battenberg-PhyloWGS from the CPC-GENE Subclonal Heterogeneity study

  Dataset EGAD00001004405

• WES raw data for study "Molecular and functional profiling of plasmablastic lymphoma"

  1 cell line and 123 patient samples including 38 normal (22 paired normal and 16 unpaired), 85 tumor-initial, FASTQ file types, Agilent SureSelect Human All Exon V6 Kit

  Dataset EGAD00001006400

• RNA-seq dataset of CD34+ HSPCs from LRMDS patients

  To profile transcriptional alterations of HSPCs in LR-MDS patients, 7AAD−CD45+Lin-CD235a−CD34+ cells were isolated from healthy donors and LR-MDS patients for RNA sequencing.

  Dataset EGAD00001015771

• The Sea Islands Genetic Network (SIGNET): Identifying genetic contributors to diabetes and dyslipidemia in African Americans

  Recent genome-wide association studies (GWAS) have successfully identified genetic variants that influence diabetes risk in European populations, however most do not have a major impact on diabetes risk in populations of African descent. The African American (AA) population from the Sea Islands of coastal South Carolina and Georgia has high rates of type 2 diabetes, low levels of admixture, and in general, consume a diet rich in saturated fats. We postulate that this unique combination of ancestral and environmental factors results in a more consistent penetrance of diabetes risk alleles, as well as enrichment of risk alleles of African origin. The existing DNA samples and rich phenotypic data from the Sea Island Families Project comprise a unique resource for genetic studies of type 2 diabetes and related metabolic traits such as dyslipidemia. Our central hypothesis is that the increased risk for T2DM in AA compared with European American (EA) is due, in part, to susceptibility alleles of African origin, and that these alleles can be identified using a GWAS. The Specific Aims are to: 1) Identify genetic risk factors for type 2 diabetes utilizing DNA samples and data from the Sea Island Families Project, Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study recruited from SC, GA, NC, and AL; and a GWAS approach; 2) Identify genetic contributors to lipoprotein subclasses in African Americans using the lipoprotein subclass profile (particle size and concentration for multiple subclasses of VLDL, LDL, and HDL) assessed by NMR at LipoScience, Inc., and the GWAS data from Aim 1. The rationale for this project is that identification and validation of novel pathophysiological pathways and informed selection of candidate genes for diabetes risk will inform development of new, targeted prevention and treatment strategies in this underserved, high risk population.

  Study phs000433

• OurHealth - Cardiovascular Disease in South Asians

  The OurHealth Study aims to build a biobank comprised of South Asian samples from participants residing in the United States. Primary objectives are to (1) identify genetic and non-genetic drivers of cardiometabolic disease in South Asians, (2) engage participants and researchers in scientific advances and research opportunities to accelerate discovery, and (3) assess the impact of returning polygenic risk scores for cardiovascular-related health conditions. Participants use a web-based platform to complete electronic informed consent, and contribute data via (1) online health surveys, (2) mailed saliva biospecimens for sequencing, and (3) optional electronic health record sharing. Surveys capture medical history, medication data, lifestyle factors, family history, mental health history, and detailed information about cultural and ancestral background. Biospecimens, procured via saliva self-collection kits, undergo DNA isolation and are sequenced using the "blended genome exome" (BGE) method, which consists of sequencing on the NovaSeqX 10B Flowcell followed by Dynamic Read Analysis for GENomics (DRAGEN) analysis for alignment to GRCh38, mapping, and variant calling. BGE uses low-coverage whole genome sequencing (lcWGS) (2-3x) combined with deep-coverage exome sequencing (30-40x), improving on SNP arrays for common variant imputation across European and non-European populations while also capturing rare coding variants. Relative to array genotyping, coverage, genotyping breadth, imputation generalizability, and cost are more optimal.BGE requires imputation for which the NHLBI TOPMed reference panel was used, and GLIMPSE2 was used for imputation emitting genotyping dosages (i.e., 0-2 multimodal continuous). Quality control (QC) included the following procedures. Sample QC excluded those with mean coverage 3% contamination from FREEMIX/VerifyBamID, sex aneuploidy and genotype/phenotype sex-mismatch due to potential phenotyping errors, fingerprinting discordance, and sample metric-level outliers were ancestry-aware, given expected distribution differences. Variant QC metrics including allele frequencies, imputation INFO scores, and Hardy-Weinberg Equilibrium (HWE) p-values are provided with the data; the genotype files provided are not filtered.

  Study phs003821

• Single Chromatin Fiber Profiling in the Human Brain

  We developed a human postmortem brain-applicable ‘Fiber-seq' protocol for genome-scale, PCR-free single molecule sequencing of on average 8-10kb long chromatin fibers, to map nucleosome positioning and nucleosome-depleted regions which include, for example, active promoters and enhancers. We generated two Fiber-seq reference sets, one from sorted non-neuronal NeuN- prefrontal cortex (PFC) nuclei from a 32 year old female donor, with total of 11,143,795 reads/fibers, and median of 30-fold genomic coverage. The other reference set was generated on sorted prefrontal NeuN+ neurons, from two 24 year old brain donors (1 female/1 male), with a combined total read/fiber count of 4,749,556 and median of 20-fold genomic coverage. Each of the peaks in the Fiber-seq libraries seq signal correlated with the ATAC peak levels in the neuronal and non-neuronal ATAC-seq libraries, respectively (promoters, clusters 1, 3; NeuN+, r = 0.574; NeuN-, r=0.683, PHowever, Fiber-seq detected 19,978 highly significant peaks which, while showing some non-significant/near-background ATAC-Seq alignments, lacked a corresponding site-specific enrichment in conventional short-read ATAC- and ChIP-seq datasets. However, 60% of these peaks were in repetitive DNA elements. Therefore, long read single chromatin fiber sequencing, which exceed the base pair length of conventional short-read libraries by two orders of magnitude, could capture many actively regulated repeat elements at the site of specific gene loci, that otherwise would remain unmappable by conventional ATAC-, and histone- ChiP-seq.

  Study phs003771

• Neoadjuvant immunotherapy leads to pathological responses in MMR proficient and MMR deficient early stage colon cancers

  PD-1 plus CTLA-4 blockade is highly effective in advanced-stage, mismatch repair (MMR)-deficient (dMMR) colorectal cancers, yet not in MMR-proficient (pMMR) tumors. We postulated a higher efficacy of neoadjuvant immunotherapy in early-stage colon cancers. In the exploratory NICHE study (ClinicalTrials.gov: NCT03026140), patients with dMMR or pMMR tumors received a single dose of ipilimumab and two doses of nivolumab before surgery, the pMMR group with or without celecoxib. The primary objective was safety and feasibility; 40 patients with 21 dMMR and 20 pMMR tumors were treated, and 3 patients received nivolumab monotherapy in the safety run-in. Treatment was well tolerated and all patients underwent radical resections without delays, meeting the primary endpoint. Of the patients who received ipilimumab + nivolumab (20 dMMR and 15 pMMR tumors), 35 were evaluable for efficacy and translational endpoints. Pathological response was observed in 20/20 (100%; 95% exact confidence interval (CI): 86–100%) dMMR tumors, with 19 major pathological responses (MPRs, ≤10% residual viable tumor) and 12 pathological complete responses. In pMMR tumors, 4/15 (27%; 95% exact CI: 8–55%) showed pathological responses, with 3 MPRs and 1 partial response. CD8+PD-1+ T cell infiltration was predictive of response in pMMR tumors. These data indicate that neoadjuvant immunotherapy may have the potential to become the standard of care for a defined group of colon cancer patients when validated in larger studies with at least 3 years of disease-free survival data.

  Study EGAS00001004160

• Oncoarray Consortium - Lung Cancer Studies

  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 substudies. The substudies that contributed include Harvard, Liverpool, Toronto, and IARC. The Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study is a randomized primary prevention trial including 29,133 male smokers enrolled in Finland between 1985 and 1993. Participants ranged between ages of 50 to 69 at enrollment and were randomized in a factorial design to take either 50 milligrams of d-alpha tocopheryl acetate (Vitamin E), 20 mg of all-trans-beta-carotene, both or placebo. The study continued to monitor cancer incidence through 2012 and total mortality through December 2013. The CAncer de PUlmon en Asturias Study (CAPUA) is a hospital-based case-control study conducted in Asturias, Spain by the University of Oviedo. Lung cancer cases were recruited in three main hospitals of Asturias, following an identical protocol from 2002 to 2012. Eligible cases were incident cases of histologically confirmed lung cancer between 30 and 85 years of age and residents in the geographical area of each participating hospital. Controls were selected from patients admitted to those hospitals with diagnoses unrelated to the exposures of interest and individually matched by ethnicity, gender, age (± 5 years) and hospital. Epidemiologic data were collected personally through computer-assisted questionnaires by trained interviewers during the first hospital admission. Structured questionnaires collected information on sociodemographic characteristics, recent and prior tobacco use, environmental exposure (air pollution and passive smoking), diet, personal and family history of cancer, and occupational history from each participant. Peripheral blood samples (or mouthwash samples when they refused to donate blood) were collected from all participants. Coding of histology was based on 2001 WHO/IASLC. Genomic DNA was extracted based on standard protocol. The Canadian Screening Study includes the nested case-control samples from 3 screening programs: IELCAP-Toronto: Ever smokers of more than 10 pack-years age 50 and above were eligible for the I-ELCAP screening program since 2003, and a total of 4782 individuals have been enrolled in the Greater Toronto Area. Participants were administered a LDCT scan along with a standard study questionnaire at baseline. Blood samples were systematically collected at baseline since 2006. Participants who had an abnormality in a CT scan were followed up every 1 to 2 years. The screening program was organized by the Princess Margaret Hospital. PanCan: Ever smokers between the ages of 50-75 with no previous history of invasive cancer are eligible to participate in the study. The study was carried out across Canada in Vancouver, Calgary, Hamilton, Toronto, Ottawa, Quebec, Halifax, and St. John's. A total of 2537 smokers have been screened from 2008 to 2011. All study participants completed a detailed questionnaire, spirometry, collection of blood specimens for biomarker measurement and LDCT at baseline. All participants are followed for a minimum of 3 years. On yearly follow up, an updated shorter questionnaire is administered, blood is collected and CT scans are performed. Blood samples are available from all 2537 individuals. BCCA Screening Program: From 1990 to 2007, 4274 smokers above 40 years old who had smoked 20 pack-years or more were enrolled at BCCA. Upon enrollment, subjects completed a questionnaire for their lifestyle and medical history. Baseline spirometry was conducted using a flow-sensitive spirometer in accordance with the American Thoracic Society recommendations. Since 2000, a LDCT was obtained in 2440 individuals. The participants were followed prospectively to determine whether they developed lung cancer. A total of 9759 individuals participated in the CT screening program in Canada from these 3 programs. The samples included in this project is based on a subset of nested lung cancer case-control pairs based on 1:2 ratio. The Carotene and Retinol Efficacy Trial (CARET) was a randomized, double-blind, placebo-controlled trial of the cancer prevention efficacy and safety of a daily combination of 30 mg of beta-carotene and 25,000 IU of retinyl palmitate in 18,314 persons at high risk for lung cancer. CARET began in 1985, and the intervention was halted in January 1996, 21 months ahead of schedule, with the twin conclusions for definitive evidence of no benefit and substantial evidence of a harmful effect of the intervention on both lung cancer incidence and total mortality. CARET continued to follow and collect endpoints on their participants through 2005. Pathology reports and medical records were reviewed to confirm cancer endpoints, and death certificates obtained to capture cause of death. During the active intervention phase of CARET, serum, plasma, whole blood, and lung tissue specimens were collected on participants. These biospecimens make up the CARET Biorepository. For the OncoArray Project, CARET provided DNA extracted from whole blood of lung cancer cases and controls matched on age at baseline (± 4 years), sex, race, baseline smoking status, history of occupational asbestos exposure (asbestos vs heavy smoker), and year of enrollment (2-year intervals). The European Prospective Investigation into Cancer and Nutrition (EPIC) study is a multi-center cohort study involving 521,000 study participants from 10 European countries. The current study involved EPIC participants from 7 countries (Greece, Netherlands, UK, France, Germany, Spain, and Italy), including 1223 incident lung cancer cases and 1249 smoking matched controls. The Kentucky Lung Cancer Research Initiative is a study conducted by the Markey Cancer Center Cancer Center and the University of Kentucky using a population-based, case-control framework to study the extraordinarily high rates of lung cancer in Southeastern, Appalachian Kentucky. Cancer cases were recruited from the Kentucky Cancer Registry at the time of diagnosis and controls were recruited from a random digit dialing process from the same region. Study accrual began in January 5, 2012 and completed on September 5, 2014 and 520 subjects were recruited in a 4:1 ratio of controls: cases from Appalachian Kentucky. Of the 520 subjects recruited, 231 are included in the OncoArray analysis, including all 93 cancer cases, and 123 controls. Newly diagnosed lung cancer cases and controls underwent blood, toenail (for trace element analysis), urine, buffy coat, water, soil, and radon collection, residence GPS mapping, as well as an extensive epidemiologic, occupational, and health history questionnaire (Clinical Trials.gov Identifier: NCT01648166). The Harvard Lung Cancer Study (HLCS) is a case-control study based at Mass General Hospital (MGH) in Boston, Massachusetts from 1992 to 2004. Details of the study were described previously. Briefly, eligible cases included any person over the age of 18 years with a diagnosis of primary lung cancer that was further confirmed by an MGH lung pathologist. Controls were recruited from the friends or spouses of cancer patients or the friends or spouses of other surgery patients in the same hospital. Potential controls were excluded from participation if they had a diagnosis of any cancer (other than non-melanoma skin cancer). Interviewer-administered questionnaires, a modified version of the standardized American Thoracic Society respiratory questionnaire, collected information on demographics, medical history, family history of cancer, smoking history, and a detailed work history, including job titles and tasks. Genome-wide genotype data were first generated using Illumina Human 610-Quad BeadChips and then imputed by MACH against the 1000 Genome Project dataset (http://browser.1000genomes.org/index.html). The Institutional Review Board of MGH and the Human Subjects Committee of the Harvard School of Public Health approved the study. The Israel study (NICCC-LCA) is an ongoing case-control study of newly diagnosed lung cancer cases of any histology and population age/sex/ethnicity-matched "healthy" controls. All participants undergo face-to-face interviews, provide a venous blood sample (separated into DNA, Sera, lymphocytes) after signing an IRB-approved form. Histology reports, FFPE blocks and clinical follow-up are available for most cancer cases. The MD Anderson Cancer Center (MDACC) Study. Lung cancer cases and frequency-matched controls were ascertained from a large ongoing case-control study at the University of Texas MD Anderson Cancer Center (UTMDACC) since 1991. Detailed study description was provided previously (Spitz et al 2007). In brief, cases were newly-diagnosed and histologically confirmed lung cancer patients recruited from UTMDACC. Controls were healthy individuals without a history of cancer (except for nonmelanoma skin cancer) and recruited from the Kelsey-Seybold Clinics, the largest private multispecialty physician group in the Houston metropolitan area. Controls were frequency-matched to cases on age (±5 years), sex, and race/ethnicity. After providing written informed consent, each study participants completed an in-person interview by staff interviewers to collect information on demographics, smoking status, etc. Blood samples were also drawn from all the study participants. This study was approved by institutional review boards of UTMDACC and Kelsey-Seybold Clinics. The Malmö Diet and Cancer Study (MDCS) is a population-based prospective cohort study that recruited men and women aged at 44 to 74 years old of living in Malmö, Sweden between 1991 and 1996. The main goal of the MDCS is to study the impact of diet on cancer incidence and mortality. It consists of a baseline examination including dietary assessment, a self-administered questionnaire, anthropometric measurements and collection of blood samples. A total of 165 incident lung cancer cases and 174 individually smoking-matched controls were available for this analysis. The Multiethnic Cohort (MEC) Study includes 215,251 men and women aged 45-74 years at recruitment, primarily from five ethnic/racial groups - African Americans and Latinos mostly recruited from CA (mainly from Los Angeles County) and Japanese Americans, Native Hawaiians and whites (mostly recruited from HI). The cohort was assembled in 1993-1996 by mailing a self-administered questionnaire to persons identified primarily through driver's license files. The baseline questionnaire obtained information on demographics, anthropometry, smoking history, medical and reproductive histories, family history of cancer, diet and physical activity. Incident cancer cases are identified by regular linkage with the State of California Cancer Registry and the Hawaii Tumor Registry, both members of the SEER Program of the NCI. In 2001-2006, a prospective biorepository was assembled by collecting a pre-diagnostic blood specimen from 67,594 surviving MEC members. At the time of blood collection a short questionnaire was administered that included information on smoking during the previous 15 days. For this study, cases were all lung cancer cases incident to blood draw and diagnosed before December 2012. For each case, a control was selected among unaffected MEC participants who were alive at time of the case's diagnosis and matched on study site, sex, race/ethnicity, age (age at diagnosis for cases; age at blood collection for controls), and date of blood collection. The Mount-Sinai Hospital-Princess Margaret Study (MSH-PMH) was conducted in the greater Toronto area from 2008 to 2013. Lung cancer cases were recruited at the hospitals in the network of the University of Toronto. Controls were selected randomly from individuals registered in the family medicine clinics databases and were frequency matched with cases on age and sex. All subjects were interviewed, and information on lifestyle risk factors, occupational history and medical and family history was collected using a standard questionnaire. Tumors were centrally reviewed by the reference pathologist, a member of the International Association for the Study of Lung Cancer (IASLC) committee, and a second pathologist in the University Health Network. If the reviews conflicted, a consensus was arrived at after discussion. Coding of histology was based on 2001 WHO/IASLC. Genomic DNA was extracted based on standard protocol. The New England Lung Cancer Study (NELCS) is a population-based case-control study of lung cancer among residents of Northern and Central New Hampshire counties and the bordering region of Vermont. Cases with histologically confirmed primary incident lung cancer were identified from 2005 to 2007 using the New Hampshire State Cancer Registry and the Dartmouth-Hitchcock Medical Center (DHMC) Tumor Registry. Control participants were identified using a commercial database and matched to lung cancer cases within 5-year age groups, sex and county. Genomic DNA was isolated from blood or buccal specimens provided by consenting participants. The study complied with requirements of the Dartmouth College's Committee for Protection of Human Subjects. The Nijmegen Lung Cancer Study. The Netherlands patients with lung cancer were identified through the population-based cancer registry of the Netherlands Comprehensive Cancer Organisation in Nijmegen, the Netherlands. Patients who were diagnosed in one of three hospitals (Radboud University Medical Center, Canisius Wilhelmina Hospital in Nijmegen, and Rijnstate Hospital in Arnhem) since 1989 and who were still alive at April 15th, 2008 were recruited for a study on gene-environment interactions in lung cancer. 458 patients gave informed consent and donated a blood sample. This case series was expanded with 94 patients to a total of 552 by linking three other studies to the population-based cancer registry in order to identify new occurrences of lung cancer among the participants of these other studies. All three other studies (i.e., POLYGENE, the Nijmegen Biomedical Study, and the Radboudumc Urology Outpatient Clinic Epidemiology Study) were initiated to study genetic risk factors for disease and participants to these studies gave general informed consent for DNA-related research and linkage with disease registries. Information on histology, stage of disease, and age at diagnoses was obtained through the cancer registry. Lifestyle information was collected through a structured questionnaire and whole blood for DNA isolation was collected by the regional thrombosis services. The cancer-free controls (46% males) were selected from participants of the "Nijmegen Biomedical Study" (NBS), an age- and sex-stratified random sample of the general population of the municipality of Nijmegen, The Netherlands. All participants provided extensive lifestyle information by structured questionnaires and blood samples for DNA isolation, serum and plasma. All controls are of self-reported European descent. The study protocols of the NBS were approved by the Institutional Review Board of the Radboudumc and all study subjects signed a written informed consent form. The Northern Sweden Health and Disease Study (NSHDS) encompasses several prospective cohorts. The current study involves participants from the Västerbotten Intervention Project (VIP), a sub-cohort within NSHDS. VIP is an ongoing prospective cohort and intervention study intended for health promotion of the general population of the Västerbotten County in northern Sweden. VIP was initiated in 1985 and all residents in the Västerbotten County were invited to participate by attending a health check-up at 40, 50 and 60 years of age. Participants were asked to complete a self-administered questionnaire including various demographic factors such as education, smoking habits, physical activity and diet. In addition, height and weight were measured and participants were asked to donate a fasting blood sample for future research. A total of 243 incident lung cancer cases and 266 individually smoking-matched controls were available for this analysis. Norway National Institute of Occupational Health Study. Early-stage NSCLC cases and healthy controls at the time of enrollment were Caucasians of Norwegian origin and were recruited from the same geographical region (Western Norway). The patients were enrolled in the study, whenever practically feasible among patients admitted for lung cancer at the Haukeland University Hospital in Bergen, Norway. The informed written consents covering analysis of molecular and genetic markers was signed by the patients prior to surgery. Only patients with histologically confirmed early-stage NSCLC were included in our study. The subjects included in this project are a subgroup recruited into the project "lung cancer genetics" at NIOH. The controls were recruited from the same geographical region of Western Norway and frequency-matched with cases on cumulative smoking dose (pack-years). Pack-years smoked [( 20 cigarettes per day) x years smoked] were calculated to indicate the cumulative smoking dose. The Cases and controls were interviewed using similar questionnaires and were categorized as never smokers, ex-smokers or current smokers. Never smokers are subjects indicating having smoked less than 100 cigarettes in their life time. Ex-smokers were defined as those having quitted at least 1 year before sampling, and current smokers were those indicating that they were smokers at the time of sampling. The project has been approved by the Regional Committee for Medical and Health Research Ethics in Southern Norway in accordance with the WMA Declaration of Helsinki. The ethical approval covered access to the NSCLC databank. The Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) Study, a randomized trial aimed at evaluating the efficacy of screening in reducing cancer mortality, recruited approximately 155,000 men and women age 55 to 74 years from 1992 to 20014. Screening for lung cancer among participants in the intervention arm included a chest x-ray at baseline followed by either three annual x-rays (for current or former smokers at enrollment) or two annual x-rays (for never smokers); participants in the control arm received routine health care. Screening-arm participants provided data on sociodemographic factors, smoking behavior, anthropometric characteristics, medical history, and family history of cancer, as well as blood samples annually for the first 6 years of the study (baseline T0 and T1 through T5). Lung cancers were ascertained through annual questionnaires mailed to the participants, and positive reports were followed up by abstracting medical records or death certificates. Follow-up in the trial as of July 2009 was 96.7%. Patients were excluded because of missing baseline questionnaire, previous history of any cancer, diagnosis of multiple cancers during follow-up, missing smoking information at baseline, missing consent for utilization of biologic specimens for etiologic studies, or unavailability/insufficient quantity of serum or DNA specimens. The Resource for the Study of Lung Cancer Epidemiology in North Trent (ReSoLuCENT) is an ongoing study conducted in Sheffield from 2006 and due to complete recruitment in 2016. The study recruited pathologically confirmed lung cancer cases diagnosed at age 60 years or younger and family matched controls. Lung cancer cases diagnosed at ages older than 60 years were recruited if they reported a family history of lung cancer. The cases and matched controls were recruited through several major cancer treatment centers, however, the majority were recruited in North Trent. All participants completed a detailed lifestyle questionnaire which included questions about occupational exposures, education, medical history and family history of cancer and lung disease. Participants also donated blood samples for DNA extraction. The ReSoLuCENT study has been funded by the Sheffield Hospitals Charity, Sheffield ECMC and Weston Park Hospital Cancer Charity. First degree relatives were removed from the sample deposited to dbGaP. The Roy Castle Lung Study of Liverpool Lung Project (LLP) is a case-control and cohort study which has recruited over 11,500 individuals since 1996 from the Liverpool region in the UK. Detailed epidemiological and clinical data is collected with associated specimens (i.e. tumor tissue, blood, plasma, sputum, bronchial lavage and oral brushings). The participants have completed a detailed lifestyle questionnaire at recruitment, with repeat questionnaires at intervals; updated data on clinical outcome and hospital events are collected through the Health and Social Care Information Center (including Office of National Statistics mortality data, Cancer Registry and 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 lung tumors were reviewed by the reference pathologist. The Seoul Bundang Lung Cancer Study was conducted between 2005 and 2010 to discover genetic and environmental factors related with lung cancer development. Lung cancer cases were recruited at the Seoul National University Hospital in Bundang. Controls were selected randomly from individuals participated in health check-up program and were frequency matched with cases on age and sex. All subjects were interviewed, and information on lifestyle risk factors, occupational history and medical and family history was collected using a standard questionnaire. Tumors were reviewed by the pathologists in the hospital. If the reviews conflicted, a consensus was arrived at after discussion. Coding of histology was based on 2001 WHO/IASLC. Genomic DNA was extracted based on standard protocol. The Shanghai Cohort Study (SCS) consisted of 18,244 men in Shanghai, China, who were 45-64 years old at the time of enrollment during 1986-1989. Approximately 80% of eligible men participated in the study. At the time of recruitment, each cohort subject was interviewed in-person by a trained nurse interviewer using a structured questionnaire that included background information, history of tobacco and alcohol use, current diet, and medical history. At the completion of the interview, the nurse collected a 10 ml blood and a single void urine specimen from the study participant. The buccal cell samples were collected from all surviving cohort members (~15,000) in the 2001-2002 follow-up interviews. The cohort has been followed for the occurrence of cancer and death through routine ascertainment of new cases from the population-based Shanghai Cancer Registry and Shanghai Vital Statistics Units. To maximize the cancer findings and minimize the loss of follow-up, we contacted each surviving cohort member annually. Retired nurses visit the last known address of each living cohort member and record details of the interim health history of the cohort member. As of December 31, 2014, cumulatively 612 (3.4%) original subjects were lost to follow-up, and 574 (3.1%) refused to our continued follow-up interview. A nested case-control study of incident lung cancer cases within the Shanghai Cohort Study was used to examine the association between serum levels of vitamin B6 and other compounds in the one-carbon metabolism pathway and risk of lung cancer. Briefly, 516 lung cancer cases were identified among cohort participants with available serum samples as of 12/31/2006. For each case, we randomly selected one control subject from all cohort members who were free of cancer and alive at the time of cancer diagnosis of the index case. Controls were matched to the index case by age at enrollment (±2 years), date of biospecimen collection (±1 month) and neighborhood of residence at recruitment, and smoking status (current, former and never smokers) as established previously for other studies. For former smokers, cases and controls were further matched by years since quitting smoking (<10 vs ≥10 years). One serum vial per subject was retrieved from biorepository and all serum samples were sent to the laboratory (B-vital) for measurements. DNA samples of 250 lung cancer cases and 250 matched controls were available for the present study. The Singapore Chinese Health Study (SCHS) cohort consisted of 63,257 Chinese men and women in Singapore when they were 45-74 years old at the time of enrollment between April 1993 and December 1998. At recruitment, each study subject was interviewed in person by a trained interviewer using a structured questionnaire that emphasized current diet assessed via a validated, 165-item food frequency questionnaire. The questionnaire also requested information on demographics, lifetime use of tobacco, incense use, current physical activity, usual sleep duration, reproductive history (women only), occupational exposure, medical history, and family history of cancer. Blood or buccal cell, and spot urine samples were collected first from a random 3% sample of cohort participants in April 1994, and extended to all surviving cohort participants starting in January 2000. Overall approximately 60% of eligible cohort participants donated biospecimens. The cohort has been passively followed for death and cancer occurrence through regular record linkage with the population-based Singapore Cancer Registry and the Singapore Registry of Births and Deaths. Migration out of Singapore, especially among housing estate residents, was negligible. As of latest update, only 55 individuals from this cohort were known to be lost to follow-up due to migration and other reason. A nested case-control study of incident lung cancer cases within the Singapore Chinese Health Study was used to examine the association between serum levels of vitamin B6 and other compounds in the one-carbon metabolism pathway and risk of lung cancer. As of 12/31/2011, 422 lung cancer cases were identified among cohort participants with available prediagnostic plasma samples. For each case, one control subject was randomly selected from all eligible cohort members who were alive and free of cancer on the date of cancer diagnosis of the index case. The control subject was individually matched to the index case by gender, dialect group (Hokkien, Cantonese), age at enrollment (±3 years), date of baseline interview (±2 year), date of biospecimen collection (±6 months), and smoking status (current, former, and never smokers). For current smokers, cases and controls were further matched by number of cigarettes per day (<15, ≥15 cigarettes/day). For former smokers, cases and controls were further matched by years since quitting smoking (<10, ≥10 years). One plasma aliquot per subject was retrieved from the biorepository and all plasma samples were sent to the laboratory (B-vital) for measurements, and one aliquot of DNA per subject for the present study. The International Agency for Research on Cancer (IARC) L2 Study. Lung cancer cases and controls were recruited through a multicentric case-control study coordinated by the IARC in Russia, Poland, Serbia, Czech Republic, and Romania from 2005 to 2013. Cases were incident cancer patients collected from general hospitals. Controls were recruited from individuals visiting general hospitals and out-patient clinics for disorders unrelated to lung cancer and/or its associated risk factors, or from the general population. Information on lifestyle risk factors, medical and family history was collected from subjects by interview using a standard questionnaire. All study participants provided written informed consent. The current study included 1,133 lung cancer cases and 1,117 controls genotyped on the Oncoarray. The Washington State University Lung Cancer Study is a hospital case-control study of 511 subjects with newly-diagnosed (within 1 year of diagnosis) lung cancer and 820 race-, sex- and age-matched controls. Lung cancer cases were recruited from lung cancer clinics within the H. Lee Moffitt Cancer Center while controls were recruited from the Lifetime Cancer Screening Center, a H. Lee Moffitt Cancer Center affiliate. None of the controls were diagnosed with any form of cancer at the time of screening. Detailed questionnaire data and oral buccal cells were collected for all subjects. The Total Lung Cancer (TLC) Study is a hospital-based study that included 458 lung cancer patients recruited for Moffitt Cancer Center's Total Cancer Care™ protocol between April 2006 and August 2010. Total Cancer Care™ is a multi-institutional observational study of cancer patients that prospectively collects self-reported demographic and clinical data, medical record information and blood samples for research purposes. All patients used in this cohort were recruited from the Thoracic Oncology Clinic at the Moffitt Cancer Center. The Vanderbilt Lung Cancer Study (BioVU) is a case-control study nested within the Vanderbilt University Medical Center biobank, BioVU. BioVU is a biorepository of DNA extracted from blood drawn from patients seeking routine clinical care at Vanderbilt University Medical Center and linked to de-identified electronic health records for research purposes. Lung cancer cases and controls were identified from BioVU participants in February 2014. Lung cancer cases were identified from the Vanderbilt tumor registry. All specimens undergo pathologic review for determination of morphology. Coding of histology was based on SEER Program Coding Guidelines. Controls were randomly selected from BioVU participants, excluding cancer patients, and were matched to cases on age (± 5 years), sex, and race. Relevant covariates were identified from electronic health records using natural language processing. Genomic DNA was extracted based on a standard protocol.

  Study phs001273

• Multi-platform genome sequencing of families with rare disease

  This dataset contains genome sequencing data from 51 individuals from 19 different family trios/quads with rare disease who consented to data sharing. PacBio Revio HiFi data (FASTQ, unaligned or aligned BAM) are available for 48 samples, and Illumina NovaSeq 6000 FASTQ data are available for 13 samples (1 trio without HiFi data, plus 10 affected probands with corresponding HiFi data).

  Dataset EGAD50000002109

• BIONi010-C-8 / SAMEA4454011 WGS data

  The iPSC line BIONi010-C-8 / SAMEA4454011 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-8 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001028

• SIGi001-A-13 / SAMEA104386250 WGS data

  The iPSC line SIGi001-A-13 / SAMEA104386250 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-13 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001031

• BIONi010-C-3 / SAMEA4342740 WGS data

  The iPSC line BIONi010-C-3 / SAMEA4342740 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-3 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001034

• BIONi010-C-7 / SAMEA4454010 WGS data

  The iPSC line BIONi010-C-7 / SAMEA4454010 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-7 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001035

• BIONi010-C-6 / SAMEA4454009 WGS data

  The iPSC line BIONi010-C-6 / SAMEA4454009 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-6 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001037

• BIONi010-C-9 / SAMEA4454012 WGS data

  The iPSC line BIONi010-C-9 / SAMEA4454012 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-9 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001040

• SIGi001-A-3 / SAMEA4448571 WGS data

  The iPSC line SIGi001-A-3 / SAMEA4448571 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-3 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001041

• BIONi010-C-4 / SAMEA4452060 WGS data

  The iPSC line BIONi010-C-4 / SAMEA4452060 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-4 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001043

• EDi014-A / SAMEA4459369 WGS data

  The iPSC line EDi014-A / SAMEA4459369 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-A is available for research use at www.EBiSC.org.

  Dataset EGAD50000001051

• EDi014-B / SAMEA4459371 WGS data

  The iPSC line EDi014-B / SAMEA4459371 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi014-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001053

• SIGi001-A-9 / SAMEA4447499 WGS data

  The iPSC line SIGi001-A-9 / SAMEA4447499 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-9 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001095

• SIGi001-A-8 / SAMEA4448777 WGS data

  The iPSC line SIGi001-A-8 / SAMEA4448777 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-8 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001093

• SIGi001-A-5 / SAMEA4448708 WGS data

  The iPSC line SIGi001-A-5 / SAMEA4448708 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-5 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001092

• SIGi001-A-4 / SAMEA4448632 WGS data

  The iPSC line SIGi001-A-4 / SAMEA4448632 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-4 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001088

• SIGi001-A-6 / SAMEA4447426 WGS data

  The iPSC line SIGi001-A-6 / SAMEA4447426 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-6 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001078

• SIGi001-A-2 / SAMEA4451116 WGS data

  The iPSC line SIGi001-A-2 / SAMEA4451116 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-2 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001077

• SIGi001-A-12 / SAMEA104237570 WGS data

  The iPSC line SIGi001-A-12 / SAMEA104237570 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-12 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001076

• SIGi001-A-11 / SAMEA4451118 WGS data

  The iPSC line SIGi001-A-11 / SAMEA4451118 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-11 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001075

• SIGi001-A-10 / SAMEA4451117 WGS data

  The iPSC line SIGi001-A-10 / SAMEA4451117 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-10 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001074

• BIONi010-C-2 / SAMEA4342705 WGS data

  The iPSC line BIONi010-C-2 / SAMEA4342705 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-2 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001068

• BIONi010-C-5 / SAMEA4452061 WGS data

  The iPSC line BIONi010-C-5 / SAMEA4452061 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-C-5 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001062

• SIGi001-A-7 / SAMEA4448730 WGS data

  The iPSC line SIGi001-A-7 / SAMEA4448730 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line SIGi001-A-7 is available for research use at www.EBiSC.org.

  Dataset EGAD50000001060

• Isotype-resolved sequencing of B-cell receptor in health and disease (2017-09-13)

  Sequencing of B-cell receptor repertoires in healthy individuals and patients with chronic lymphocytic leukemia. 1) 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 please see http://www.sanger.ac.uk/datasharing/ This dataset contains all the data available for this study on 2017-09-13.

  Dataset EGAD00001003748

• X Ten analysis of spiked placental tissue samples

  Metagenomics data of 80 placental tissue samples analyzed by X Ten for their possible microbial content. These 80 samples from pre-labor C-section deliveries, representing Cohort 1, were spiked with 1100 CFU Salmonella bongori. These same samples were also analyzed by 16S amplicon sequencing (search for ERP109246 in ENA).

  Dataset EGAD00001004198

• Normal sample for patient SA655

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA655

  Dataset EGAD00001009251

• Normal sample for patient SA665

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA665

  Dataset EGAD00001009252

• Normal sample for patient SA667

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA667

  Dataset EGAD00001009253

• Normal sample for patient SA668

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA668

  Dataset EGAD00001009254

• Normal sample for patient SA669

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA669

  Dataset EGAD00001009255

• Normal sample for patient SA671

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA671

  Dataset EGAD00001009256

• Normal sample for patient SA672

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA672

  Dataset EGAD00001009257

• Tumour sample for patient SA1035

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1035

  Dataset EGAD00001009258

• Tumour sample for patient SA994

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA994

  Dataset EGAD00001009259

• Tumour sample for patient SA604

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA604

  Dataset EGAD00001009260

• Tumour sample for patient SA605

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA605

  Dataset EGAD00001009261

• Tumour sample for patient SA609

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA609

  Dataset EGAD00001009262

• Spatially resolved cellular and molecular drivers of cardiac remodelling in healthy and failing human hearts: Adult RNA (2025-07-31)

  Cell Atlas of the diseased human heart. 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 2025-07-31.

  Dataset EGAD00001015668

• WGS FASTQ files studied in A first-in-human clinical study of an allogenic iPSC-derived corneal endothelial cell substitute transplantation for bullous keratopathy

  This data set contains 2 paired fastq files (WGS).

  Dataset EGAD50000000947

• johannesburg_20150706_X

  Genotype data and (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 750 individuals from Respiratory and Meningeal Pathogens Unit in Soweto, South Africa - X chromosome.

  Dataset EGAD00010002580

• Target pilot trial

  In vitro and in vivo drug screens of tumor cells identify novel therapies for high-risk child cancer

  Dataset EGAD00001008358

• Covacta RNAseq counts

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes read counts per gene. Read counts were generated for the Gencode v27 annotation using the summarize Overlaps method from bioC in mode “IntersectionStrict”

  Dataset EGAD00001011164

• Mayo Clinic and Illumina Collaborative Early Stage Ovarian Cancer (ESOC) Study

  Twenty five patients with early stage carcinoma (Stage I and II) of the ovary were consented for this study. As part of a collaborative agreement with Illumina Inc, Tumor-DNA and patient matched normal DNA from blood underwent whole genome sequencing and microarray genotyping and RNA underwent RNASeq. Tissue also underwent IHC staining for TP53 mutations. The aim of the study was to profile the genomic landscape of these early tumors to discover biomarkers for early detection or subgrouping into different genomic or outcome subgroups. Analyses performed include somatic mutation analysis, RNASeq mutation analysis, LOH analysis, structural variant detection. The current release of this study focusses on 17 patients with serous carcinoma and stage 1 or 2 and with high grade (3 or 4).

  Study phs000897

• Circulating cell-free DNA analysis in Small Cell Lung Cancer

  Small cell lung cancer (SCLC) accounts for ~250,000 deaths worldwide each year. Acquisition of adequate tumour biopsies is challenging and liquid biopsies present the best option for patient stratification and response monitoring. We present genome-wide and targeted plasma DNA sequencing data that identifies tumour related changes in 91% of limited (LS-SCLC) and 100% of extensive stage (ES-SCLC) patients. Parallel analysis of circulating tumour cells (CTCs, by CellSearch) based on ≥ 1 CTC/7.5ml blood increased tumour detection frequencies to 98% patients (95% for LS-SCLC) where CTC count and plasma DNA readouts correlated with disease stage and overall survival (OS). Targeted plasma DNA sequencing identified potential therapeutic targets in >50% of patients. This approach will support trials of targeted therapies where improved patients outcomes are urgently required.

  Study EGAS00001003110

• Integration of Clinical and Molecular Biomarkers for Melanoma Survival (Berwick)

  The long-term goal of the InterMEL Program Project: Integration of Clinical and Molecular Biomarkers for Melanoma Survival is to identify molecular and clinical factors that predict survival of melanoma patients. Our overarching hypothesis is that we can identify factors in the primary melanoma tumor that will lead to more aggressive disease. Melanoma patients diagnosed at American Joint Committee on Cancer (AJCC) tumor, lymph nodes, and metastases (TNM) stages IIA/IIB/IIC/IIIA/IIIB/IIIC/IIID display highly variable clinical outcomes and responses to therapy. We wish to identify robust and reproducible biomarkers or sets of classifiers that distinguish patients likely to have poor prognosis. These biomarkers will help establish targets for adjuvant therapies for this set of patients before the tumors metastasize. Aim 1. Classify actionable somatic mutations, and copy number variations (CNVs) in relationship to melanoma survival. In Project 1, Targeted Sequencing and Clinicopathology to Evaluate Primary Melanoma Molecular Subtypes and Outcomes, we will profile 468 genes using the MSKIMPACT ™ assay and identify somatic mutations and CNVs associated with melanoma-specific survival, as well as their co-occurrence with other mutations, in 1,000 tumors from patients at AJCC TNM stages IIA-IIID: approximately 500 from patients who died with melanoma within five years and approximately 500 from individuals who have lived at least five years. We will also evaluate the joint effects of somatic mutations, CNVs and pathologic characteristics associated with good and poor outcomes. Aim 2. Identify primary melanoma DNA methylation profiles to evaluate subtypes and survival. Although it has been established that melanomas frequently have aberrant DNA methylation, it is unknown if DNA methylation in primary melanomas predicts outcome. In Project 2, Primary Melanoma DNA Methylation Profiling for Evaluating Subtypes and Survival, we will profile the same primary melanomas as in Project 1 with Illumina Infinium 850K methylation arrays. We expect to: identify and characterize DNA methylation-based melanoma subclasses; train, test and validate a CpG signature prognostic for survival from melanoma; determine whether this profile adds information to outcome prediction beyond AJCC TNM staging. This project is based on the hypothesis that DNA methylation in primary melanoma will define subgroups (including a poor-prognosis CIMP – ‘CpG island methylator phenotype' subtype) and that a CpG signature will be prognostic for melanoma survival. Aim 3. Define microRNA expression changes in relation to melanoma survival. MicroRNAs have been associated with poor prognosis in melanoma, as well as in other cancers. In Project 3, Prognostic and Functional Role of a Gene Expression Signature in Melanoma Patients, we hypothesize that altered miRNA expression, captured at the time of diagnosis, may contribute to the aggressive behavior of a subset of early stage primary melanomas. We will profile the same primary melanomas as in Projects 1 and 2 with a Nanostring assay. This project will define and validate a tissue-based microRNA signature in conducted to determine whether the prognostic miRNA signature, as well as other candidate genes emerging from other projects, contribute to melanoma survival. Aim 4. Integrate data from multiple platforms to identify melanoma subtypes and survival. Despite substantial literature on gene tumor mutation-, methylation- and gene expression-based prognostic and predictive signatures for melanoma, few such signatures are used in clinical practice. Project 4, Multiplatform Analysis of Melanoma Molecular Subtypes and Patient Survival Outcome, will use novel integrative clustering methods to identify molecular subtypes of melanoma jointly defined across these platforms.

  Study phs003099

• RNA-seq

  Our cohort represents infants with ALL in whom KMT2Ar was not detected by FISH or by standard cytogenetics. Whole-transcriptome sequencing (WTS) libraries were prepared using the NEBNext Ultra II RNA Directional library kit for samples with at least 100ng RNA (n=19), the Clontech double stranded cDNA conversion kit plus the Nextera XT library protocol for samples with less than 100ng RNA (n=4), or ribodepletion using NEBNext rRNA Depletion Kit v2 (Human/Mouse/Rat) for Total RNA (n=1). Libraries were paired-end sequenced using the Illumina HiSeq 2500.

  Dataset EGAD50000000595

• RNAseq of baseline tumor tissue obtained during TUR to identify biomarkers for ICB response in MIBC

  RNAseq of baseline tumor tissue obtained during TUR to identify biomarkers for ICB response in MIBC. Constitutes the entire NABUCCO phase 1B clinical trial cohort. The NABUCCO 1 trial contains 18 single-end RNA sequenced samples and 6 paired end RNA sequenced samples. The NABUCCO 2 trial contains 25 paired end RNA sequenced samples. The file type for all of the samples is FASTQ. For single end RNA sequencing, Illumina HiSeq 2500 was used as the sequencing platform. For paired end RNA sequencing, the Illumina NovaSeq 6000 was used as the sequencing platform.

  Dataset EGAD50000002556

• Capture-based Methods for Transcriptomic Profiling of FFPE material

  This dataset includes all FASTQ files for 11 samples where different capture-based methods for transcriptome profiling have been tested. Specifically, we have the 'traditional' RNA-seq experiment with fresh frozen (FF) material, and 3 different capture methods for the matching formalin-fixed paraffin-embedded samples: Agilent (AGI), IDT, and Twist Biosciences (TBS). In total, there are 43 samples with paired-end FASTQ files (1 sample did not have sufficient material to test all methods). Samples are identified by the R01-R11 IDs with a suffix that indicates the capture method used (or FF for fresh frozen).

  Dataset EGAD00001007655

• Whole genome sequencing

  Whole genome sequencing of high-grade serous ovarian cancer (HGSC) tumours and matched normals from 15 patients with homologous recombination deficiencies. The dataset includes fastq files from 56 HGSC tumours (1 primary, 1 relapse, 54 end-stage) and 15 matched normals. Sequence libraries were generated from tumour and matched normal genomic DNA using the KAPA HyperPrep PCR-free library preparation kit (Roche), or the Illumina TruSeq DNA Nano kit according to manufacturer’s instructions. Sequencing was carried out by the Kinghorn Centre for Clinical Genomics Sequencing Laboratory (Sydney, Australia) on the HiSeq X Ten System (Illumina) or by the Australian Genome Research Facility (Melbourne, Australia) on an Illumina NovaSeq to a minimum base coverage of 30-fold for normal DNA and 60-fold for tumour DNA samples.

  Dataset EGAD00001009746

• National Cancer Institute Genome-Wide Association Study of Renal Cell Carcinoma

  The National Cancer Institute (NCI) genome-wide association study (GWAS) of renal cell carcinoma (RCC) was conducted to investigate common genetic variants associated with RCC risk. The GWAS includes 1,453 RCC cases and 3,531 controls of European background from 4 studies (3 cohort, 1 case-control), scanned using the Illumina InfiniumHumanHap 550, 610 and 660W chips. This project was supported by the Intramural Research Program of the National Institutes of Health and NCI. Data from this GWAS were pooled with those from another GWAS of RCC (2,639 cases and 5,392 controls) conducted in Europe by the International Agency for Research on Cancer and the Centre National de Gènotypage. Findings from this collaboration are described in an upcoming report (Purdue et al. Nature Genetics 2011;43(1):60-65; PMID: 21131975). Only data from the NCI scan are included in this dbGaP submission.

  Study phs000351

• Genomic Correlates of Response and Resistance to Immune Checkpoint Blockade in Solid Tumors

  Immune checkpoint inhibitors yield clinical benefit in many cancer types, but molecular predictors of response have not yet been robustly characterized. In this study, we pursued whole exome sequencing (WES) of pre-treatment tumors from patients treated with immune checkpoint therapies - including monoclonal antibodies targeting programmed cell death-1 (PD-1) and cytotoxic T-lymphocyte-associated protein-4 (CTLA-4). Using these data, we aim to apply computational pipelines for mutation-calling, neoantigen prediction, and other analyses to validate pre-existing hypotheses regarding response to immune checkpoint therapies and discover new relationships with greater power. Further, by pursuing genomic characterization of tumors from patients with a variety of cancer types, we hope to describe molecular features of intrinsically sensitive or resistant tumors that are both context-specific and shared across cancer types.

  Study phs001565

• Natural History of and Genetic Modifiers in Spinocerebellar Ataxias

  Spinocerebellar ataxias (SCA) are genetic neurological diseases that cause imbalance, poor coordination, and speech difficulties. There are different kinds of SCA and this study will focus on types 1, 2, 3, and 6 (SCA 1, SCA 2, SCA 3, also known as Machado-Joseph disease and SCA 6). The diseases are rare, slowly progressive, cause increasingly severe neurological difficulties and are variable across and within genotypes. The purpose of this research study is to bring together a group of experts in the field of SCA for the purpose of learning more about the disease. The research questions are: How does the disease progress over time? What are the best ways to measure disease progression? Do some genes, other than the gene that is abnormal in the SCA disease, have any effect on the way the disease behaves?

  Study phs001332

• NHLBI TOPMed - NHGRI CCDG: Malmo Preventive Project (MPP)

  The Malmö Preventive Project (MPP) was a community-based disease prevention program including 33,346 inhabitants from the city of Malmö in Southern Sweden. Complete birth cohorts between 1921-1949 were invited, and the participation rate was 71%. Participants underwent screening between 1974 to 1992 for cardiovascular risk factors, alcohol abuse, and breast cancer. Between 2002-2006, surviving participants were invited to a reexamination which included blood sampling from which DNA has been extracted. Subjects with prevalent or incident AF were identified from national registers as previously described, and cases with DNA were then matched in a 1:1 fashion to controls with DNA from the same cohort by sex, age (±1 year), and date of baseline exam (±1 year). Also, controls required a follow-up exceeding that of the corresponding AF case.

  Study phs001544

• The function of circular RMST in neuroendocrine tumours

  Circular RNA (circRNA) is a class of noncoding RNA with regulatory potentials. Its role in the transdifferentiation of prostate and lung adenocarcinoma into neuroendocrine prostate cancer (NEPC) and small cell lung cancer (SCLC) remains unexplored. Here we identified circRMST as an exceptionally abundant circRNA predominantly expressed in NEPC using total RNA-seq profiling of patient samples. In addition, circRMST is also abundantly expressed in SCLC. Functional studies using shRNA, siRNA, CRISPR-Cas13 and Cas9 consistently demonstrate that circRMST is essential for tumour growth and the expression of ASCL1, a master regulator of neuroendocrine fate. Mechanistically, circRMST physically interacts with lineage transcription factors NKX2-1 and SOX2. Loss of circRMST induces NKX2-1 protein degradation through autophagy-lysosomal pathway and alters the genomic binding of SOX2, collectively leading to the loss of ASCL1 transcription.

  Study EGAS50000000897

• SC_DDD-G-1

  Batch 1 of unfiltered genotype data for DDD Study patients (N=2,997), some of which were used in the neurodevelopmental disorder discovery GWAS (Niemi et al., Nature 2018). Samples were genotyped on the Illumina HumanCoreExome BeadChip. QC'd data is available in release EGAD00010001604

  Dataset EGAD00010001598

• scRNAseq of ALS patients

  The data set contains information from 9 individuals (5 ALS + 4 controls) using single cell RNA sequencing in combination with TCR V(D)J sequencing to study the immune profile of the central nervous compartment (CSF). Sequencing was done using 10x Genomics platform (5’ scRNAseq & V(D)J Reagent Kits v1.1). 5P and TCR libraries were then pooled and for sequencing on the NovaSeq sequencer. Provided files are in .fastq.gz format and per individual four files are available (Read 1&2 and Lane 1&2).

  Dataset EGAD00001009623

• Solve-RD_GENTURIS_cohort-1_DF1+2_V1

  Solve-RD data submitted to the ERN-GENTURIS cohort for re-analysis (Data freeze 1+2) v1

  Dataset EGAD00001009767

• GWAS for Membranous Nephropathy

  Primary membranous nephropathy (MN) is a rare autoimmune cause of kidney failure. This dataset is from a genome-wide association study (GWAS) designed to identify novel genetic risk loci for MN. The provided cohort (named as European-1 Cohort) is composed of 611 cases of primary MN and 1,246 healthy controls of European ancestry. This cohort was used in the GWAS meta-analysis, as described in the manuscript entitled "Genetic architecture of membranous nephropathy and its potential diagnostic implications" (Nature Communications 2020, in press).The genome-wide summary statistics, including trans-ethnic meta-analysis across 8 GWAS cohorts of European and East Asian ancestry and ethnicity specific meta-analyses, are freely available for download on the Kiryluk lab website: http://www.columbiamedicine.org/divisions/kiryluk/resources.php.

  Study phs001984

• Discovery and validation of an ancillary genomic test of malignancy for primary melanocytic tumors

  Background:Pathological diagnosis of melanocytic tumors can be difficult and prone to error. More accurate and reliable ancillary investigations than those currently available are required to improve diagnostic accuracy. Goals: (1) to generate a genomic model for distinguishing benign (nevi) from malignant (melanoma) melanocytic skin tumors, developed from a customized gene panel evaluated on a cohort of 250 nevi and melanomas. (2) To evaluate the performance of the genomic model in melanocytic tumors of uncertain diagnosis/behavior. Details: The cohort of 250 melanomas and naevi was split into a discovery set and a validation set. Our genomic model obtained an area under the curve of 95% in the discovery cohort and 96% for the validation cohort. Based on a Youden index threshold, the resulting classifier shows high specificity (>95% in the discovery and validation cohorts), with sensitivities >80% in the discovery and validation cohorts. Evaluation of the genomic model on a cohort of 110 melanocytic tumors identifies key driver mutations in agreement with the likely pathway of origin of the tumors. The probability of melanoma (p=0.02) from the genomic model was significantly associated with pathology-based estimates of malignancy for melanocytic tumors lacking pathway-defining genomic aberrations (conventional tumors). The genomic model identified 8/36 (22%) conventional tumors with unresolved malignancy to have a high probability of melanoma, with 7/8 of these cases showing negative/non-aberrant results with either fluorescent in-situ hybridization, PRAME and/or p16 immunostains. Furthermore, no evidence of malignant behavior based on the genomic model was seen in 4 conventional borderline tumors with more than 1 year follow-up. Conclusion: This genomic model can become a clinically useful ancillary tool that is highly specific for differentiating melanomas from nevi.

  Study EGAS50000000887

• scRNA-seq dataset, RCC

  scRNA-seq dataset for the study "Surgery in combination with immune checkpoint therapy as an effective treatment for patients with metastatic cancer." The dataset comprises 38 samples from 19 patients, with each pair includes a baseline (BL) sample and a post-biopsy or post-surgery sample. Each sample corresponds to an R1 (read 1) and an R2 (read 2) files (.fastq.gz) for paired reads. Beside procedure (biopsy or surgery), another important phenotype is response (PR and PD in this case, no SD for these patients), included in the description of the samples. The sequencing was performed using Illumina NovaSeq 6000 platform., as seen in the experiment description.

  Dataset EGAD50000000566

• Characterization of Neoantigen-reactive T cells by Single-Cell Analysis

  Through CITE-seq and TCR-seq analysis of non-small cell lung cancer (NSCLC) tumor-infiltrating lymphocytes (TIL), we developed a neoantigen-reactive T-cell signature based on clonotype frequency and CD39 protein and CXCL13 mRNA expression. There are four datasets from four NSCLC cases. Each dataset includes (1) Transcriptome of tumor infiltrating lymphocytes (TIL), (2) Cell surface protein expression on TIL by Feature barcoding, (3) T-cell receptor analysis of TIL, and (4) Reference file for feature-barcoding antibodies.

  Study phs002792

• Breast Cancer Genome Guided Therapy Study (BEAUTY)

  The Breast Cancer Genome Guided Therapy Study (BEAUTY) is a prospective neoadjuvant clinical study enrolling 140 women with Stage I-III breast cancer. The goals of this study were to 1) perform comprehensive sequencing of germline and tumor tissues (exome and RNA seq), 2) identify genomic alterations and perturbed pathways associated with response/resistance to standard chemotherapy, and 3) develop patient-derived xenograft (PDX) for testing of therapeutic regimens chosen on the basis of alterations identified by genetic sequencing.

  Study phs001050