14977 results for "cancer studies using rna-seq"

in 50.36 milliseconds.

• Tandem duplication of chromosomal segments is common in ovarian and breast cancer genomes

  Tandem duplication of chromosomal segments is common in ovarian and breast cancer genomes

  Dataset EGAD00001000050

• Evaluation of Ancestry Admixture among Chileans

  The purpose of this study is to investigate ancestry admixture among Chileans with and without gallbladder cancer.

  Study phs001385

• WGS data of non-small cell lung cancer samples

  Paired-end WGS data from 118 non-small cell lung cancer samples from 49 patients. WGS was performed on Illumina NovaSeq 6000.

  Dataset EGAD50000000639

• Whole genome sequencing of a breast cancer cohort with known functional homologous recombination status

  41 breast cancer patients with known functional homologous recombination status (matched normal and tumor genomes, n=82)

  Dataset EGAD00001008027

• Sequence of breast cancer bone metastases PDX from 2 targeted panels

  Targeted sequencing analyses was made on samples of PDX engrafted with breast cancer bone metastases, 2 PDX acquired resistance to palbociclib.

  Dataset EGAD00001006070

• Exome sequencing to evaluate HER2/ERBB2 mutations in cancer

  ERBB2/HER2 transmembrane and juxtamembrane domain mutations in cancer. Exome sequencing of tumor and matched blood and 2 blood samples from relatives.

  Dataset EGAD00001004351

• Germline whole exome sequencing in testicular cancer

  This dataset contains variant call format files generated from whole exome sequencing of germline DNA from indiviudals with diagnosed with testicualr germ cell cancer.

  Dataset EGAD00001004345

• Multi-omics Profiling of Asian Breast Cancers

  Whole exome and transcriptome sequencing data of primary tumors from 178 Korean breast cancer patients.

  Study EGAS00001002621

• whole genome sequencing of breast cancer cell lines and patient derived xenograft models

  whole genome sequencing of six commonly used breast cancer cell lines and six patient derived xenograft models

  Dataset EGAD00001008802

• Treated and control Patient Derived Xenografts of colorectal cancer (CRC) samples

  Bank of treateed and control PDXs metastastic colorectal cancer sample RNAseq

  Dataset EGAD00001010022

• RNAseq analysis on primary sites Colorectal Cancer xenografts (PRX) samples

  Bank of primary sites (PRs) colorectal cancer of Patient Derived Xenografts (PDXs)

  Dataset EGAD00001010101

• Spatial TCR sequencing in breast cancer

  Spatial characterization by TCR sequencing in tumor core and matched stroma in seven cases of triple negative breast cancer.

  Dataset EGAD00001010203

• Sequence of breast cancer bone metastases PDX from 2 targeted panels

  Sequence of breast cancer bone metastases PDX obtained by 2 targeted panels

  Dataset EGAD00001010856

• Shallow-whole genome sequencing for copy numbers in resectable gastric cancer treated with surgery alone

  Shallow-whole genome sequencing for copy numbers in resectable gastric cancer treated with surgery alone

  Dataset EGAD00001011994

• Geographic variation of mutagenic exposures in kidney cancer genomes – structural variation vcf files (Mutographs)

  Geographic variation of mutagenic exposures in kidney cancer genomes – structural variation vcf files ( Mutographs )

  Dataset EGAD00001013726

• Geographic and age-related variations in mutational processes in colorectal cancer - filtered vcf files (Mutographs)

  Geographic and age-related variations in mutational processes in colorectal cancer - filtered vcf files (Mutographs)

  Dataset EGAD00001015486

• Genetic Basis of Breast Cancer Resistance in BRCA1 Mutation Carrier

  Our study addressed a specific question in NCI RFA-CA-12-022: "What underlying causal events - e.g., genetic, epigenetic, biologic, behavioral, or environmental - allow certain individuals to survive beyond the expected limits of otherwise highly lethal cancers?". A germline mutation in BRCA1 (BRCA1+) is the most penetrant genetic predisposition for breast cancer. Nevertheless, a portion of BRCA1+ carriers does not develop breast cancer in their lifetime, suggesting that the genetic predisposition can be antagonized by resistant factors. BRCA1+ was inherited from an ancestor of the carrier family thousand years ago. We hypothesize that evolution could select certain genetic components to suppress oncogenesis caused by the predisposition. We compared germline variants in all genes in 27 pairs of breast cancer-unaffected and -affected BRCA1+ carriers, each pair inherited the same BRCA1+. We identified 12 deleterious variants enriched in breast cancer-unaffected carriers, all are common variants. A variant rs3735400 is located in ANLN, a cytokinesis-essential gene. Overexpression of variant-containing ANLN and suppressed expression of endogenous ANLN decrease ANLN nuclear localization and delay cell growth. Our findings suggest that common variants can be selected to resist oncogenesis imposed by BRCA1+.

  Study phs001243

• A panel of reference haplotypes for imputing complement component 4 (C4) gene structural variation

  Neuropsychiatric and autoimmune disorders have substantial epidemiological correlations (Benros et al., JAMA Psychiatry 2013, PMID: 23760347) and broad, genome-wide patterns of shared genetic risk (Pouget et al., Hum Mol Genet, PMID: 31211845; Tylee et al., Am J Med Genet B Neuropsychiatr Genet 2018, PMID: 30325587). Some cases of psychosis involve autoantibodies against the NMDA receptor, AMPA receptor, or other synaptic proteins (reviewed in Dalmau et al, Lancet Neurol 2011, PMID: 21163445). The related autoimmune conditions lupus and Sjogren's Syndrome also involve the development of autoantibodies. The possibility that neuropsychiatric disorders can have molecular mechanisms in common with autoimmune disorders - for example, that psychosis involves an inflammatory or autoimmune component in some patients, or that immune molecules are re-used in the brain to underlie other important biological activities (Stevens et al., Cell 2007, PMID: 18083105) - could open novel therapeutic possibilities for neuropsychiatric disorders. At a genetic level, the strongest genetic associations of schizophrenia, lupus, and Sjogren's Syndrome to common genetic variation involve associations to genetic markers in the Major Histocompatibility Complex (MHC) locus. Bipolar disorder in some studies also associates with variation in or near the MHC locus, though less strongly than schizophrenia does. Intriguingly, the same specific SNPs appear to associate strongly with schizophrenia, lupus, and Sjogren's; these strongly associating SNPs span a genomic segment that includes the HLA class II genes (which have an important role in antibody production) and the complement component 4 (C4) genes. The specific genes and alleles responsible for these associations need to be completely defined, and the extent to which they represent shared or distinct genetic influences in neuropsychiatric and autoimmune illnesses needs to be clarified. The complement component 4 (C4A and C4B) genes are present in the MHC locus, between the class I and class II HLA genes. C4A and C4B commonly vary in genomic copy number and encode complement proteins with distinct affinities for molecular targets. The complex genetic variation at C4 - arising from many alleles with different numbers of C4A and C4B genes - has been challenging to analyze in large cohorts. We recently developed an approach to this problem based on imputation: people share long haplotypes with the same combinations of SNP and C4 alleles, such that C4A and C4B gene copy numbers can be imputed from SNP data (Sekar et al., Nature 2016, PMID: 26814963). In the current work, to analyze C4 in large cohorts, we developed a way to identify C4 alleles from whole-genome sequence (WGS) data, then analyzed WGS data from 1,234 individuals to create a large multi-ancestry panel of 2,530 reference haplotypes of MHC SNPs and C4 alleles that can then be imputed into still-larger cohorts for which SNP data are available. With this dbGaP submission, we make this reference panel available for other studies. Protocols and software for imputing C4 alleles into genome-wide SNP data, and for performing molecular analyses on the C4 genes (such as direct measurement of copy number from genomic DNA), can be found on the McCarroll Lab web site (http://mccarrolllab.org/resources). We are also working to create additional reference panels for imputation of C4 alleles that will be based on still-larger and more diverse population samples; links to these will also be available on the McCarroll Lab web site as we create and validate them.

  Study phs001992

• Coronary Artery Risk Development in Young Adults (CARDIA-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Related Studies: Other CARDIA data available include:phs000236.v2.p2 PAGE: CALiCo: Coronary Artery Risk Development in Young Adults(CARDIA) phs000309.v3.p2 The CARDIA-GENEVA Study phs000399.v1.p2 NHLBI GO-ESP: Heart Cohorts Exome Sequencing Project (CARDIA) phs000613.v1.p2 NHLBI CARDIA Candidate Gene Association Resource (CARe) phs003675.v1.p1 CARDIA Multi-omics Obesity & CVD Substudy – Year 20 Untargeted Metabolomics Data phs001612.v3.p2 NHLBI TOPMed: CARDIA (Coronary Artery Risk Development in Young Adults) phs003045.v1.p1 Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Coronary Artery Risk Development in Young Adults Study (CARDIA) phs000285.v4.p3 CARDIA_Cohort Available Data: Available data for request include exam data through Year 30 and outcomes and death data through 2022. Additionally, data from 28 ancillary studies are available for request.Objectives: The original objectives of CARDIA were to document levels of risk factors for coronary artery disease and potential determinants of these risk factors in young adults; to study the interrelationships of risk factors and lifestyles and to document behavioral and environmental changes during the transition from young adulthood to middle age; to compare cross-sectional and longitudinal data on age-related trends in cardiovascular disease risk factors; and to compare levels and evolution of risk factors between men and women, blacks and whites, and in groups of differing socioeconomic status. Goals of the study have evolved to emphasize understanding determinants of left ventricular mass, emerging obesity and hypertension, and sequelae of hypertension in pregnancy.Background: CARDIA is designed to increase understanding of contributors to changes in cardiovascular disease (CVD) risk factors during the critical years of transition from young adulthood to middle age. CARDIA was funded initially in 1983 for a five-year cycle that included two rounds of examinations. Contract renewals have allowed for subsequent re-examinations.Participants: Black and white men and women; ages 18-30 years at entry with a range of attained education; original sample size: 5,115.Design: CARDIA is a population-based observational study of 5,115 participants aged 18-30 years recruited in 1985-1986. The sample was designed to achieve approximately balanced subgroups of race, gender, education (high school or less and more than high school) and age (18-24 and 25-30). Forty percent of the cohort had no more than a high school education. A total of nine examinations have been completed in the cohort with examination cycles at year 2 of the project and years 5, 7, 10 , 15, 20, 25, and 30.In addition to standard measurements of blood pressure, anthropometry, blood lipids, smoking behavior, physical activity, diet, pulmonary function, and many psychological factors, CARDIA has other included measurements (in subsets or in the full cohort) to obtain unique information on other aspects of risk factor development and early morbidity. These have included: graded exercise treadmill testing; echocardiography, particularly for measurement of left ventricular mass; cardiovascular reactivity; serum cotinine; Lp(a), apoE phenotype, apolipoprotein A1 and B; homocysteine; skin reflectance; body composition by dual X-ray absorptiometry; glucose tolerance testing; vascular resistance and compliance; and plasma renin activity and sympathetic nervous system activity.

  Study phs003739

• RNAseq of preneoplasia lung adenocarcinoma

  RNA sequencing of 168 pulmonary samples including lung preneoplasia atypical adenomatous hyperplasia (AAH, N=38), adenocarcinoma in situ (AIS, N=22), minimally invasive adenocarcinoma (MIA, N=19) and invasive lung adenocarcinoma (ADC, N=38) and adjacent lung tissues (Normal, N=62).

  Dataset EGAD50000000395

• Single-cell RNA sequencing data of patients with T follicular helper cell lymphomas

  This dataset contains single-cell count data generated by the Cellranger pipeline (v3.1.0, 10X Genomics) from 9 LN and 16 PB samples of 14 patients with T follicular helper cell lymphomas (TFHLs) as well as 7 homeostatic LN (HLN) samples.

  Dataset EGAD50000000402

• Pregnancy-associated melanoma

  The aim of this project is to assess differences in intratumoral immune composition in pregnant melanoma patients versus non pregnant melanoma controls. Samples (N=25) were obtained from a local patient database. From archived FFPE we isolated RNA and performed NGS and bio-informatica data-analysis.

  Dataset EGAD50000000706

• RNAseq of samples from CLL patients treated with ibrutinib in vivo

  The dataset contains RNA sequencing data from 22 paired samples of 11 patients before and during ibrutinib therapy (median time on therapy 2 weeks; range 1-12 weeks). The sequencing was performed in two batches.

  Dataset EGAD50000000879

• Altered Blood and Keratinocyte microRNA/transfer RNA Fragment Profiles Related to Fibromyalgia Syndrome and its Severity

  We show dysregulated microRNA and tRNA fragment profiles related to FMS pathopyhsiology and opening new perspectives for FMS diagnostics and symptom monitoring. This dataset includes all sequencing raw files from whole blood (tempus tube) and keratinocyte sequencing.

  Dataset EGAD50000000900

• Melanoma transcriptomic data from patients undergoing immunotherapy

  This dataset contains raw RNA sequencing data from melanoma patient tumor samples collected before and during immunotherapy. The data support investigation of treatment-related changes in tumor cell populations. Samples were analyzed as part of a study exploring cellular responses to immune-based therapies.

  Dataset EGAD50000001569

• Shallow Whole Genome Sequencing (sWGS) of pancreatic ductal adenocarcinoma

  Associated with CNA differences between RNA-based subtypes of PDAC. Shallow Whole Genome Sequencing (sWGS) generated 47 .bam files from 37 patients. sWGS was used for Copy number aberrations (CNA) determination.

  Dataset EGAD50000001732

• miRNA-sequencing of PBMCs from COVID-19 patients experiencing different degrees of the disease (mild and critical), and control patients

  micro RNA-sequencing of peripheral blood mononuclear cells collected from mild COVID-19 (n = 6), critical COVID-19 (n = 13) and control (n = 8) patients. Sequencing data is provided as FASTQ files.

  Dataset EGAD50000001406

• Clonal_analysis_Bcell_activation

  We developed a B cell stimulation protocol that allowed us to expand a smaller number of naive B cells in culture (2,000 B cells at day 0). On day 6, we performed single-cell RNA-and BCR-sequencing on the entire culture, preserving both clonal diversity and size.

  Dataset EGAD50000002114

• MPNST_Data

  WES from 51 cases initially diagnosed as Malignant Nerve Sheath Tumours (MPNST) and RNA sequencing data from 10 MPNST cases. Find more information in article: Lyskjær et al, 2020, J Pathol, "H3K27me3 expression and methylation status in histological variants of malignant peripheral nerve sheath tumours".

  Dataset EGAD00001006253

• Transcriptomic origins of mpMRI visibility

  We profiled the transcriptomes (RNA-sequencing) of 40 clinically significant invisible and visible tumors, all with ISUP Grade 2 disease and treated by radical prostatectomy. Twenty tumors were mpMRI invisible (PI-RADSv2: 1-2), while 20 tumors were visible (PI-RADsv2: 5).

  Dataset EGAD00001004397

• Genomic Landscape of Radiation Induced Meningiomas

  EGAS00001002317 - Whole exome sequencing of data of 18 RIMs with matched bloods. Median depth of 112x (range of 110-120). Performed on Illumina HiSeq Platform. EGAS00001002318 - RNA sequencing data of 18 RIMs on the Illumina HiSeq Platform.

  Dataset EGAD00001004358

• Vγ9Vδ2-T cells in chronic lymphocytic leukemia patients and healthy controls

  RNA sequencing data from Vγ9Vδ2-T cells from chronic lymphocytic leukemia patients and age-mnatched healthy controls. Matched Vγ9Vδ2-T cell samples before and after expansion with autologous monocyte-derived dendritic cells for each donor are included.

  Dataset EGAD00001004325

• Single-cell Transcriptome for glioblastoma intra-tumoral heterogeneity

  Single-Cell RNA Sequencing of 355 cells isolated from 7 tissue fragments of 3 patients corresponding to locally adjacent tumor, multifocal with recurrence and sections segregated by a marker of tumor cellularity (5-ALA).

  Dataset EGAD00001002249

• Single-cell RNA sequencing of bronchoalveolar lavages from COVID-19 patients

  Discriminating mild-moderate from critical COVID-19 disease by innate and adaptive immune single-cell profiling of bronchoalveolar lavages.

  Study EGAS00001004717

• Mantle cell lymphoma primary cases RNAseq data

  Dataset includes fastq transcriptomic sequencing files from 8 conventional (SOX11+) and 4 non-nodal (SOX11-) mantle cell lymphoma (MCL) primary cases. RNA-sequencing has performed from peripheral blood and lymph node diagnostic samples.

  Dataset EGAD00001009422

• RNASeq read files of renal cell carcinoma PDX samples

  This dataset contains 56 fastq files of paired-end RNA sequencing of a Illumina® TrueSeq stranded mRNA library of 28 renal cell carcinoma PDX samples.

  Dataset EGAD00001008766

• Potent neutralizing antibodies against SARS-CoV-2

  The COVID-19 pandemic urgently needs therapeutic and prophylactic interventions. Here we report the rapid identification of SARS-CoV-2 neutralizing antibodies by high-throughput single-cell RNA and VDJ sequencing of antigen-enriched B cells from 60 convalescent patients.

  Dataset EGAD00001006130

• Homozygous inactivation of CHEK2 is linked to a familial case of multiple primary lung cancer with accompanying cancers in other organs

  In clinical practice, there are a number of cancer patients with clear family histories, but not belonging to existing familial malignancies. Recent advances in genomic technologies have enhanced the possibility of identifying causative genes in such cases. Two siblings, an elder sister and a younger brother, were found to have multiple primary lung cancers at the age of 60. The former subsequently developed breast cancer, and had a history of myoma uteri. The latter had initially developed prostate cancer at the age of 59, and had a history of colon cancer. SNP genotyping revealed that approximately 10% of the genomes were homozygous in both patients. Exome sequencing revealed non-synonymous mutations in four genes in the runs of homozygosity: CHEK2, FCGRT, INPP5J, and SFI1. Evolutionary conservation of primary protein structures suggested the functional importance of the CHEK2 mutation, R474C. This mutation altered the tertiary structure of CHK2 by disrupting the salt bridge between R474 and E394. No such structural changes were observed with the other three mutated genes. Subsequent cell-based transfection analysis revealed that CHK2 R474C was unstable and scarcely activated. We concluded that CHEK2 is a causative gene in this case of familial cancer. Although homozygous inactivation of CHEK2 in mice led to cancers in multiple organs, accumulation of additional human cases is needed to establish its pathogenic role in humans.

  Study JGAS000057

• Dynamic Evolution of Fibroblasts Revealed by Single Cell RNA Sequencing of Human Pancreatic Cancer

  Understanding the constituents of the pancreatic ductal adenocarcinoma (PDAC) microenvironment may illuminate more efficacious targets for treating this aggressive malignancy. However, the compositional changes occurring in untreated and treated PDAC relative to both normal and inflamed pancreas have not been well characterized. To provide a more comprehensive understanding of the PDAC tumor microenvironment relative to the non-cancerous pancreas, we performed single-cell expression profiling (10X Genomics Chromium) on samples of upfront resectable PDAC, FOLFIRINOX-based treated PDAC, chronic pancreatitis, and normal pancreas specimens from 19 patients. Spatial gene expression profiling (10X Genomics Visium) was performed to gain additional insight into cell populations. Our analysis revealed that fibroblasts are central mediators of cell-cell communication in both inflamed and malignant settings and defined unique roles for these cell populations in different disease contexts.

  Study phs003751

• Microarray_cases

  CASE SAMPLES USING Affymetrix SNP6.0 technology (Thermo Fisher Scientific company): OncoScan FFPE Assay Kit was used for FFPE tissue samples (designed for degraded DNA) and the Cytoscan HD Array Kit was used for the fresh-frozen tissues

  Dataset EGAD00010002034

• Nanopore sequencing of brain tumor tissue obtained by cavitating ultrasonic aspiration

  This dataset contains 21 pediatric brain tumor cases which where obtained during surgery using a cavitating ultrasonic aspiration and submitted to nanopore whole genome sequencing.

  Dataset EGAD50000000269

• OXEL pilot WES data

  This dataset contains aligned BAM files from whole-exome sequencing of 29 patients from the Oxel pilot study. Alignment to GRCh38 reference genome was performed using the BWA aligner.

  Dataset EGAD50000000327

• H3Africa ACEGID H3Africa Array Genotype

  SNP Genotyping for Lassa Fever cases and population controls from Nigeria and Sierra Leone using Illumina H3Africa array version 1

  Dataset EGAD00010002510

• Whole genome sequencing profiling of patient-derived organoids (PDO)

  Whole genome sequencing profiling of 41 PDAC patient-derived organoids (PDO) - WGS unmapped reads, sequenced using NovaSeq 6000, 15x coverage 160 million reads per sample.

  Dataset EGAD50000000280

• N2M2 methylation array data

  Methylation profiling of 228 samples, using the approach described in "Molecularly matched targeted therapies plus radiotherapy in patients with newly diagnosed glioblastoma without MGMT promoter hypermethylation (N2M2/NOA-20 phase I/IIa umbrella trial)"

  Dataset EGAD00010002747

• WES_dataset1

  Fourteen MEITLs and one EATL previously had been sequenced using the SureSelectXT Target Enrichment System (Agilent Technologies, Santa Clara, CA, USA).

  Dataset EGAD50000001620

• LBC1921 gvcfs

  297 members of the LBC1921 were sequenced using the Illumina HiSeq X platform. This dataset contains the gvcfs.

  Dataset EGAD00001006416

• Whole Exome Sequencing of gliomas

  15 whole exome sequencing datasets from five patients. Data is provided as bam files. Libraries were generated using the SeqCap EZ Exome v3.0 kit and sequenced on an Illumina sequencer

  Dataset EGAD00001003763

• 666PG SNVs

  SNV calls generated using SomaticSniper in VCF format from the CPCGene 666PG study

  Dataset EGAD00001006148

• Whole genome sequencing in myasthenia gravis

  This dataset contains whole genome sequencing data on 25 individuals with myasthenia gravis. The data was generated using Illumina sequencing technology and is presented as BAM files for each sample.

  Dataset EGAD00001005262

• 666PG indels

  Indel calls generated using Pindel in VCF format from the CPCGene 666PG study

  Dataset EGAD00001006147

• Macrophage response in term and preterm infants

  The data set comprises 48 samples from term and preterm infants. Expression profiles were generated using different stimuli (O2 3%, 21%, 65%; LPS stimulation).

  Dataset EGAD00001006885

• Saliva microbiota in Finnish children

  The saliva microbiota of 972 Finnish children, aged 9-14 years was characterized using the 16S rRNA (V3-V4) gene sequencing with Illumina Hiseq platform.

  Dataset EGAD00001004145

• Microbial infections in Alzheimer’s patients

  In the present study, we have examined fungal and bacterial infection in brain tissue from 10 AD patients and 16 control subjects by next-generation sequencing NGS using MiSeq sequencing platform (Illumina).

  Dataset EGAD00001003886

• Copy Number Variation using Affymetrix Optima Array

  Diagnostic yield of affymetrix optima microarray in patients with non-syndromic autism spectrum disorders in India.

  Study EGAS00001006439

• 666PG Somatic CNA calls

  Filtered somatic CNA calls detected using Battenberg from the CPCGGene 666PG study

  Dataset EGAD00001007699

• WCDT Hi-C assays performed mCRPC biopsies - Part 2

  13 paired FASTQ files from a Hi-C assay performed on mCRPC tumors. Sequencing was performed using 150nt paired reads generated by a Novaseq 6000 instrument.

  Dataset EGAD00001009417

• HIV positive individuals (first batch)

  Contains 30x coverage whole genome sequence data from 40 HIV+ South Africans. Samples sequenced using Illumina HiSeq. BAM files have been uploaded. Sequenced at Edinburgh Genomics.

  Dataset EGAD00001007589

• Copy number profiling using PlasmaSeq

  In order to establish copy number profiles from the various samples we prepared libraries and subjected them to whole-genome sequencing at a shallow sequencing depth (0.1x)

  Dataset EGAD00001000761

• Accurate mapping of mitochondrial DNA deletions and duplications using deep sequencing

  The dataset comprises of muscle samples from three patients with mitochondrial disease: Patient 1, age9; Patient 2, age16; and Patient 3, age 58.

  Dataset EGAD00001006079

• PBMCs of HCC Patients treated with anti-PD1 ICB

  10 samples (one baseline, 9 on-treatment). Fastq files containing 5'GEx data, prepared using 10x Genomics pipeline, sequenced on Illumina HiSeq4000.

  Dataset EGAD00001006645

• GECCO: Detecting Common and Rare Genetic Loci and GxE Interactions in Colorectal Cancer

  COLON, Colorectal Cancer: Longitudinal Observational study on Nutritional and lifestyle factors that influence colorectal tumor recurrence, survival and quality of life: The COLON study is a multi-center prospective cohort study to assess the role of diet and other lifestyle factors in cancer recurrence and survival among incident colorectal cancer patients in the Netherlands. DACHS, Darmkrebs: Chancen der Verhütung durch Screening:This German study was initiated as a large population-based case-control study in 2003 in the Rhine-Neckar-Odenwald region (southwest region of Germany) to assess the potential of endoscopic screening for reduction of colorectal cancer risk and to investigate etiologic determinants of disease, particularly lifestyle/environmental factors and genetic factors. During an in-person interview, data were collected on demographics, medical history, family history of CRC, and various life-style factors, as were blood and mouthwash samples. EPIC, European Prospective Investigation into Cancer: EPIC is an on-going multicenter prospective cohort study designed to investigate the associations between diet, lifestyle, genetic and environmental factors and various types of cancer. HPFS, Health Professionals Follow-up Study: HPFS is a parallel prospective study to the NHS. The HPFS cohort comprised 51,529 men aged 40-75 who, in 1986, responded to a mailed questionnaire. Participants provided information on health related exposures, including current and past smoking history, age, weight, height, diet, physical activity, aspirin use, and family history of colorectal cancer. Colorectal cancer and other outcomes were reported by participants or next-of-kin and were followed up through review of the medical and pathology record by physicians. Overall, more than 97% of self-reported colorectal cancers were confirmed by medical record review. Information was abstracted on histology and primary location. Follow-up evaluation has been excellent, with 94% of the men responding to date. NHS, Nurses' Health Study: The NHS cohort began in 1976 when 121,700 married female registered nurses age 30-55 years returned the initial questionnaire that ascertained a variety of important health-related exposures [PMID:248266]. Since 1976, follow-up questionnaires have been mailed every 2 years. Colorectal cancer and other outcomes were reported by participants or next-of-kin and followed up through review of the medical and pathology record by physicians. Overall, more than 97% of self-reported colorectal cancers were confirmed by medical-record review. Information was abstracted on histology and primary location. The rate of follow-up evaluation has been high: as a proportion of the total possible follow-up time, follow-up evaluation has been more than 92%. NQplus, Nutrition Questionnaires plus: NQplus is a longitudinal observational study on diet and health in the general Dutch population.

  Study phs001315

• GAW16 Framingham and Simulated Data

  Important links to apply for individual-level data Genetic Analysis Workshop Instructions to Request Authorized Access Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Research Use Statement Questions regarding GAW16 should be directed to Vanessa Olmo at vanessa@business-endeavors.com. Problem 2: Description of the Framingham Heart Study In GAW16, we use data drawn from the Framingham Heart Study. The Framingham Heart Study — under the direction of National Heart, Lung, and Blood Institute; NHLBI — began in 1948 with the recruitment of adults from the town of Framingham, Massachusetts. At the time, little was known about the general causes of heart disease and stroke, but the death rates for cardiovascular disease (CVD) had been increasing steadily since the beginning of the 20th century and had become an American epidemic. The Framingham Heart Study is now conducted in collaboration with Boston University. The objective of the Framingham Heart Study was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Between 1948 and 1953 the researchers recruited 5,209 subjects (2,336 men and 2,873 women) between the ages of 29 and 62 from the town of Framingham, Massachusetts and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Subjects were recruited from lists of addresses recorded for the town. Two out of every three households were approached for participation in the study. While there was no intention to recruit families for family studies, the plan was to recruit all household members in the ages 30-60 within each house that was selected for study. Hence, many biologically related individuals were recruited, including 1644 spouse pairs. Since 1948, these participants have returned to the study every two years for a detailed medical history, physical examination, and laboratory tests. Now in 2008 at 60 years of follow up, there remain about 500 participants from this cohort. Between 1971 and 1975 the study enrolled a second-generation group — 5,124 of the original participants' children and the spouses of these children — to participate in similar examinations. 2,616 subjects are offspring of the original spouse pairs and 34 are stepchildren. A total of 898 offspring are children of cohort members where only one parent was a study participant and 1,576 are spouses of the offspring. The Offspring Cohort has been followed every four years through 2001 (except between Exams 1 and 2 with an intervening 8 years) using protocols similar to those used for study of the Original Cohort. Between 2002 and 2005 the study enrolled the third generation (Gen3) of the Framingham Heart Study - 4095 offspring of the second generation. None of their spouses were recruited. An additional 103 parents of this third generation, who were not recruited between 1971 and 1975, were also recruited at this time. The latter group is not included in the GAW16 data. With the recruitment of this third generation, the study has increasingly focused on genetic factors associated with the development of cardiovascular disease and its associated risk factors. To date, there is only one examination of this generation of participants. A description of the recruitment of this third generation and comparison with the earlier generations at their initial recruitment is presented in Splansky GL et al., 2007. Further information on the Study can be found at http://www.nhlbi.nih.gov/about/framingham/index.html. Genome-wide Dense SNP Scan in Framingham Heart Study Genetic studies did not begin in the FHS until the 1990s. In the late 1980s and through the 1990s DNA was extracted from blood samples of surviving FHS participants. In 2007, the FHS entered a new phase with the conduct of genotyping for the FHS SHARe (SNP Health Association Resource) project, for which dense SNP genotyping was performed using approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel) in 10,775 samples (some duplicates) from the three generations of subjects (including over 900 pedigrees). Affymetrix conducted all genotyping for the FHS SHARe project, using the 250K Sty, 250K Nsp, and the supplemental 50K platforms. Eighty-nine percent of the DNA samples were collected during the 1990s. To maximize the power of the study, we also extracted DNA from 1133 blood samples, drawn from subjects who had no DNA, to include in the SHARe project. These samples had been sitting in our refrigerators for some time, a few as far back as the 1970s. We refer to these DNA samples as the legacy samples. These samples had a higher failure rate in the genotyping process (40%) than the other eighty-nine percent (3%). Affymetrix invoked its own criteria for a sample to succeed in genotyping. All non-legacy samples must succeed on all three platforms, while legacy samples needed to pass on at least one platform. When a sample failed, additional attempts were made. Samples that repeatedly failed 2-4 times were called failures. Other samples failed due to issues of genotyped sex identification not matching our records or low SNP concordance among SNPs common across arrays or contamination. Eighty-nine percent of the legacy samples for which genotyping results are available passed all three platforms. The genotyping data from the 10,043 samples from 9354 subjects that passed the Affymetrix criteria were additionally checked for gender consistency and consistency with family structure, resulting in genotyping data for 9,274 participants in FHS SHARe. Genotype calls were made with the BRLMM algorithm. The SHARe database is housed at the National Center for Biotechnology Information database of genotypes and phenotypes (NCBI dbGaP) and contains all ~550,000 SNPs. This genome-wide dense SNP scan and a subset of phenotypes from the Framingham Heart Study are the focus of the Genetic Analysis Workshop 16. Further information on the specific variables in the Problem 2 dataset can be found by clicking on the Documents tab at the top of the page. Problem 3: Description of the Simulated Data Set The focus of this simulation is gene discovery in genome-wide association scans (GWAS). The Framingham Heart Study data set (distributed as "Problem 2") is the basis for the FHS* simulated data. The pedigree structures are derived from the data distributed for Problem 2, and we distribute an accompanying triplet file (triplet_sim) containing person ID, father ID, mother ID, to ensure the identical subjects, pedigrees, and singletons are used in the simulated data analysis. Consistent with standard practice, founders and singletons are designated as subjects with both fshare and mshare equal to zero (missing). The simulated data includes a total of 6,479 subjects with both phenotype and genotype data, in 942 pedigrees distributed among 3 generations and 188 singletons. Data inclusion is consistent with the subjects' consent for use by both for-profit and not-for-profit researchers. The genotypes for all Problem 3 replicates are fixed as measured and distributed for Problem 2 for both the genomewide scan and the additional candidate gene SNPs, for a total of approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel). Thus, to analyze the Problem 3 simulated data you also will need to download the Problem 2 genotypes. Note that there are slight discrepancies in counts between Problems 2 and 3 due to a change in consents between the two datasets. Several phenotypes that contribute to coronary heart disease (CHD) were simulated for all individuals with genotypes across three different time points, 10 years apart. All genotyped individuals have complete data; the effects of missing values can be investigated by user-specified missing value patterns. There are 200 longitudinal datasets created, based on the generating model, and each replication is found in a separate dataset. We suggest that if only one replication is to be analyzed, that it be replication 1 to enable more precise comparisons among analytical approaches. The 'shareid' will allow you to merge the simulated phenotype data with the Problem 2 genotype data, and reconstruction of the pedigrees using the distributed 'triplet_sim' file or for larger families' relationships with the triplet distributed with the Problem 2. The simulated data problem is further described in the associated readme file, and a data dictionary is provided defining all the variables. For disclosure of the generating model for these data, please contact Jean MacCluer at jean@sfbrgenetics.org.

  Study phs000128

• 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

• Maintenance of Genome Sequence Integrity in Long- and Short-lived Rodent Species

  In this study, we compared somatic mutation frequencies and spectra of bleomycin-treated and control fibroblasts of 5 species, i.e., mouse, guinea pig, blind mole-rat, naked mole-rat and humans, by using single-cell whole-genome sequencing. Sequencing data of the human cells are deposited here in the dbGaP. Sequencing data of the rodent cells are in the SRA database, under accession ID: PRJNA753541.

  Study phs002610

• Single-Cell DNA Methylation Profiling with sciMETv2

  In this study we developed a high-throughput single-cell DNA methylation analysis technology, sciMETv2. This technique is rapid, cost-effective, and robust, enabling large-scale single-cell methylome dataset generation. We demonstrate this technology on human middle frontal gyrus, where we identified major cell types. We additionally performed target enrichment using sciMET-cap to enable a reduction in sequencing costs per cell while achieving comparable cell type identification.

  Study phs003091

• Identification Of Pathogenic Mutations And Application Of Polygenic Risk Scores In Early-Onset Diabetes Patients

  Maturity-onset Diabetes of the Young (MODY) presents a diagnostic challenge. In this study we investigate the genetic background of Latvian early-onset diabetes patients, using whole-genome sequencing data. Additionally, we investigate the utility of previously published and available type 1 diabetes (T1D) and type 2 diabetes (T2D) polygenic risk scores in differentiating monogenic diabetes (MODY) from T1D and T2D cases.

  Study EGAS50000000991

• CLDN14 mutation identifed from Japanese sensorineural hearing loss patient.

  The CLDN14 gene, encoding claudin 14, is reported to be one of the rare causes of non-syndromic autosomal dominant sensorineural hearing loss. The detailed clinical characteristics of CLDN14 associated hearing loss is still remain unclear. In the present study, we performed CLDN14 mutation analysis using massively parallel DNA sequencing (MPS) to reveal the clinical characteristics of CLDN14-related hearing loss in a large hearing loss population.

  Study JGAS000191

• Exome_sequencing_of_Congenital_Heart_Disease_families_from_the_Competence_Network_Berlin

  This project aims to study exomes from families and trios withcongenital heart disease (CHD). The samples have been collected underthe Competence Network - Congenital Heart Defects in Berlin, Germany.The phenotypes are mainly left ventricular outflow obstruction (aorticstenosis, bicuspd aortic valve disease coarctation and hypoplasticleft heart), but will also include samples with hypoplastic rightheart and atrioventricular septal defects. We will perform whole exomesequencing using Agilent sequence capture and Illumina HiSeqsequencing.

  Study EGAS00001000368

• Study_to_investigate_the_prevalence__of_leukaemic_mutations_in_whole_blood_DNA_in_a_cohort_of_blood_donors

  The aim of this study is to ascertain whether leukaemic mutations exist within the blood of people with otherwise normal haematopoeisis. To satisfy this aim we plan to look for 7 known leukaemic mutations in the whole blood DNA of a large cohort of blood donors who have normal haematopoesis. Genomic regions around mutational sites have been amplified using a 2 step PCR process which involves barcoding of individual patients

  Study EGAS00001000814

• Mutation_analysis_in_human_iPS_cells_

  PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced by MiSeq. 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/

  Study EGAS00001000359

• UAMS Smoldering Myeloma Timeline Cohort

  To better understand the pattern of genetic changes over time, we performed whole exome sequencing of sequential bone marrow samples from 9 patients taken overtime including some paired SMM/newly diagnosed MM/Relapse MM samples. Samples from 9 patients (9 controls and 53 tumors) underwent whole exome sequencing with an additional capture for the IGH, IHK, IGL, and MYC loci. DNA was obtained from either CD138+ cells from the bone marrow of smoldering myeloma patients through time (tumor) or from stem cell harvests or peripheral blood cells from the same patient (control). 100 ng of DNA was fragmented, end-repaired, and adapters ligated using NimbleGen's MedExome. After PCR amplification hybridized libraries underwent further amplification before being sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads.

  Dataset EGAD00001005056

• Genomic alterations in MM - BAM

  Tumor DNA was extracted from 100 bone marrow aspirate samples where CD138+ selection had been performed to enrich plasma cells from patients with multiple myeloma. Patient matched control DNA from either peripheral blood leukocytes or CD34+ stem cell harvests was also isolated. Both tumor and control DNA underwent library preparation using the Hyperplus kit (KAPA Biosystems) and were hybridized to baits for a targeted SeqCap myeloma panel (Nimblegen) encompassing 129 genes, regions for SNPs for copy number determination, and the IGH, IGK, IGL loci, as well as approximately 5 Mb surrounding the MYC locus. Samples were sequenced on a HiSeq2500 using 100 bp paired end reads. Resulting BAM files were returned along with annotations for somatic events including single nucleotide mutations, indels and structural rearrangements.

  Dataset EGAD00001004117

• ExomeSeq-EGAS00001001306

  Exome Sequencing. 3 μg of genomic DNA from each sample were sheared and used for the construction of a paired-end sequencing library as described in the paired-end sequencing sample preparation protocol provided by Illumina41. Enrichment of exonic sequences was then performed for each library using either the Sure Select Human All Exon 50 Mb or All Exon+UTRs v4 kits following the manufacturer’s instructions (Agilent Technologies). Exon-enriched DNA was pulled down by magnetic beads coated with streptavidin (Invitrogen), followed by washing, elution and 18 additional cycles of amplification of the captured library. Enriched libraries were sequenced (2 × 76 bp) in one lane of an Illumina GAIIx sequencer or in two lanes of a HiSeq2000 when using pools of eight samples.

  Dataset EGAD00001001464