Search Results - EGA European Genome-Phenome Archive

Single-nuclei histone modification profiling of the adult human central nervous system unveils epigenetic memory of developmental programs

We profile the adult human CNS from distinct regions, sex and ages, for chromatin accessibility at the single-nuclei level. Tissue was collected from 20 different donors (10 male, 10 female) within the ages of 34 to 74 years old. Additionally we performed Single-cell nanoCUT&Tag H3K27ac and H3K27me3 profiling for 4 of the donors and multiome single cell assay (RNA-seq+ATAC-seq) for 2 of the donors. Each donor donated fresh frozen white matter from the following three tissue regions: primary motor cortex (Brodmann area 4, BA4), arbor vitae cerebelli (CB) and fasciculi cuneatus and gracilis from and cervical spinal cord (CSC). Tissue was processed semi-randomly, ensuring that each batch of experiments had a representation of both sexes and all three tissue regions. Completed libraries were again randomly multiplexed during sequencing to minimize batch effects. We also performed micro-C,2 replicates, of iPS human derived cell cultures of human oligodendrocyte precursor cells (hOPC).

Dataset EGAD50000000410

Combination pembrolizumab and radiotherapy induces systemic anti-tumor immune responses in immunologically-cold non-small cell lung cancer

The abscopal effects of radiation may sensitize immunologically “cold” tumors to immune checkpoint inhibition (ICI). We investigated the immunostimulatory effects of radiotherapy leveraging multi-omic analyses of serial tissue and blood biospecimens (n=293) from a phase 2 clinical trial of stereotactic body radiation therapy (SBRT) followed by pembrolizumab in metastatic non-small cell lung cancer (NSCLC; NCT02492568). Patients with immunologically-cold tumors (low tumor mutation burden, null PD-L1 expression, WNT-pathway mutated) in the SBRT arm had significantly longer progression-free survival compared to ICI alone (P<0.05). Induction of interferon-gamma, interferon-alpha, and antigen processing and presentation gene sets was significantly enriched post SBRT in non-irradiated tumor sites (FDR adjusted P<0.01). Significant on-therapy expansions of new and pre-existing TCR clones in both the tumor and blood compartments were noted in the SBRT arm (P<0.05). These findings support the systemic anti-tumor effects of immuno-radiotherapy and may open a therapeutic window of opportunity to overcome resistance to ICI.

Dataset EGAD50000000404

Subclonal diversification of primary breast cancer

Cancers are ecosystems of genetically related clones, competing across space and time for limited resources. To understand the clonal structure of primary breast cancer, we applied genome and targeted sequencing to 295 samples from 49 patients’ tumors. The extent of subclonal diversification varied considerably among patients and encompassed many spatial patterns, including local growth, intraductal dissemination and clonal intermixture. Landmarks of disease progression, such as acquiring invasive or metastatic potential, arose within detectable subclones of antecedent lesions, suggesting that subclonal mutations could be relevant if actionable. No defined temporal order of mutation was evident, with the commonest genes, including PIK3CA, TP53, BRCA2, PTEN and MYC, mutated early in some, late in others, often exhibiting parallel evolution across subclones. Signatures of homologous recombination deficiency correlated with response to neoadjuvant chemotherapy. Thus, the interplay of mutation, growth and competition drives clonal structures of breast cancer that are complex, variable across patients and clinically relevant.

Dataset EGAD00001000898

Whole genome and whole transcriptome sequencing of patients diagnosed with angiosarcoma.

Angiosarcomas are rare, clinically-aggressive tumors with a predilection for the elderly and immunosuppressed, which has incited suspicion of an oncogenic virus. We studied the metagenomic landscape of angiosarcomas and identified reads mapping to human herpesvirus-7 (HHV-7). Overall, HHV-7 was present in two-thirds of angiosarcomas, particularly in cases with low tumor mutation burden and lacking signatures of ultraviolet-induced DNA damage. Transcriptomic profiling revealed the enrichment of tumor inflammation signatures in HHV7-positive angiosarcomas. In conclusion, we identified a distinct “inflammatory” subtype of angiosarcoma associated with HHV-7.

Study EGAS00001003895

Identification of hypermutation and defective mismatch repair in ctDNA from metastatic prostate cancer

DNA mismatch repair defects (MMRd) and tumor hypermutation are rare and under-characterized in metastatic prostate cancer. Furthermore, since hypermutated MMRd prostate cancers can respond to immune checkpoint inhibitors, there is an urgent need for practical detection tools. We analyzed cell-free DNA targeted sequencing data from 434 metastatic prostate cancer patients with circulating tumor DNA (ctDNA) purity above 2%. Samples with somatic hypermutation were subjected to 150x whole exome sequencing. These data allowed us to interrogate the salient genomic properties of this rare prostate cancer subtype and correlate findings with patient clinical outcomes.

Study EGAS00001003899

Somatic mutations and clonal dynamics in healthy and cirrhotic human liver

Chronic liver injury predisposes to cirrhosis and hepatocellular carcinoma, but how somatic mutations accumulate in liver disease is unexplored. We sequenced whole genomes of 400 microdissections of 100-500 hepatocytes from 5 normal and 6 cirrhotic livers. Compared to normal liver, cirrhotic liver had higher mutation burden, especially structural variants, including chromothripsis. Cirrhotic nodules were oligoclonal; sometimes entirely derived from a single, recent common ancestor. Clonal expansions millimeters in diameter occurred in cirrhosis in the absence of known driver mutations. Endogenous mutational processes predominated, although signatures of polycyclic aromatic hydrocarbon and aristolochic acid exposure occurred in some samples. Up to 10-fold within-patient variation in activity of exogenous signatures existed between adjacent cirrhotic nodules, with both clone-specific and microenvironmental forces shaping this heterogeneity. Synchronous hepatocellular carcinomas drew from the same repertoire of mutational signatures as background cirrhotic liver, but with higher burden. Somatic mutations chronicle the exposures, toxicity, regeneration and clonal structure of liver tissue as it progresses from health to disease.

Dataset EGAD00001004578

Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities

Despite molecular and clinical heterogeneity, small cell lung cancer (SCLC) is treated as a single entity with predictably poor results. Using tumor expression data, we applied non-negative matrix factorization, which identified four SCLC subtypes defined largely by differential expression of transcription factors ASCL1, NEUROD1, and POU2F3 or low expression of all three transcription factor signatures accompanied by an Inflamed signature (SCLC-A, N, P and I, respectively). The presence of these subtypes were then validated in tumor gene expression data from the IMpower133 clinical trial.

Study EGAS00001004888

scRNA-seq of patient-derived PDAC organoids and matched CAFs

We established direct three-dimensional (3D) co-cultures of primary PDAC organoids and patient-matched CAFs. Single-cell RNA sequencing was performed for three organoid/CAF pairs in mono- and co-culture to uncover transcriptional changes induced by tumor-stroma interaction. Single-cell RNA sequencing data evidenced induction of a pro-inflammatory phenotype in CAFs in co-cultures. Organoids showed increased expression of genes associated with epithelial-to-mesenchymal transition (EMT) in co-cultures and several potential receptor-ligand interactions related to EMT were identified, supporting a key role of CAF-driven induction of EMT in PDAC chemoresistance.

Study EGAS00001006661

Personalized Onco-Genomic Project for pediatric and adolescent patients in British Columbia

This is an extension of the BC Cancer Agency's Personalized Onco-Genomics (POG) project to children and adolescents treated at BC Children's Hospital. The project provides access to whole genome and transcriptome sequencing, and integrated bioinformatics analyses, of relapsed, refractory or poor prognosis cancers with an aim to identify actionable variants that can inform clinical decision making.

Study EGAS00001006967

Chromatin accessibility maps of chronic lymphocytic leukemia identify subtype-specific epigenome signatures and transcription regulatory networks

Chronic lymphocytic leukemia (CLL) is characterized by substantial clinical heterogeneity, despite relatively few genetic alterations. To provide a basis for studying epigenome deregulation in CLL, we established genome-wide chromatin accessibility maps for 88 CLL samples from 55 patients using the ATAC-seq assay, and we also performed ChIPmentation and RNA-seq profiling for ten representative samples. Based on the resulting dataset, we devised and applied a bioinformatic method that links chromatin profiles to clinical annotations. Our analysis identified sample-specific variation on top of a shared core of CLL regulatory regions. IGHV mutation status – which distinguishes the two major subtypes of CLL – was accurately predicted by the chromatin profiles, and gene regulatory networks inferred for IGHV-mutated vs. IGHV-unmutated samples identified characteristic differences between these two disease subtypes. In summary, we discovered widespread heterogeneity in the chromatin landscape of CLL, established a community resource for studying epigenome deregulation in leukemia, and demonstrated the feasibility of chromatin accessibility mapping in cancer cohorts and clinical research.

Dataset EGAD00001002110

Sequencing component for the whole genome methylation analysis in PBMCs and cell subsets (pilot study)

DNA methylation has been shown to play a major role in determining cellular phenotype by regulating gene expression. Moreover, dysregulation of differentially methylated genes has been implicated in disease pathogenesis of various conditions including cancer development as well as autoimmune diseases such as systemic Lupus erythematosus and rheumatoid arthritis. Evidence is rapidly accumulating for a role of DNA methylation in regulating immune responses in health and disease. However, the exact mechanisms remain unknown. The overall aim of the project is to investigate the role of epigenetic mechanisms in regulating immunity and their impact on autoimmune disease pathogenesis.The aim of this pilot study is to perform whole genome methylation analysis in peripheral blood mononuclear cells (PBMCs) and cell subsets (CD4, CD8, CD14, CD19, CD16 and whole PBMCs) obtained from 6 healthy volunteers. Whole genome methylation analysis will be performed using two methodological approaches, the Infinium Methylation Bead Array K450 (Illumina) and MeDIP-seq. mRNA expression arrays will also be performed in order to correlate DNA methylation with gene expression as well as genotyping on the Illumina OmniExpress chip

Dataset EGAD00001000394

FASTQ files of the small RNA-Seq dataset from the POPS cohort

Placental biopsies were collected within 30 minutes of birth and flash frozen in RNAlater(ThermoFisher). For each biopsy,total placental RNA was extracted from approximately 5 mg of tissue using the “mirVana miRNA Isolation Kit” (Ambion) followed by DNase treatment (“DNA-free DNA Removal Kit”, Ambion). RNA quality was assessed with the Agilent Bioanalyzer and all the samples with RIN values ≥ 7.0 were used in the downstream experiments. Total RNA-libraries were prepared from 300-500ng of total placental RNA with the “TruSeq Stranded Total RNA Library Prep Kit with Ribo-Zero Human/Mouse/Rat”(Illumina). Small RNA-libraries were prepared from 150ng of total placental RNA with the “NEBNext Multiplex Small RNA Library Prep Kit for Illumina”(New England Biolabs)and concentrated using the “QIAquick PCR purification kit”(Qiagen). Paired libraries were combined and size selected using the Pippin Prep and 3% Agarose Gel Cassette with marker F (Sage Science),pooled and sequenced (single-end, 50bp) using a Single End V4 cluster kit and HiSeq4000 instrument.

Dataset EGAD00001004860

MARS-seq dataset of five obese human subjects and a lean human subject

Biopsies from visceral adipose tissue from the omental depot (OAT) were obtained from five obese individuals and one lean donor with participant informed consent obtained after the nature and possible consequences of the studies were explained under protocols approved by the Institutional Review Boards of the Perelman School of Medicine at the University of Pennsylvania, the Children’s Hospital of Philadelphia, or the Tel Aviv Sourasky Medical Center. The obese donors underwent bariatric surgery, the lean donor underwent cholecystectomy. OAT samples were placed in 1 mL of DMEM, and finely minced under sterile conditions before digestion in 50 mL of DMEM with 3 mg/1 mL collagenase IV (Gibco). Samples were incubated at 37°C in a rotating oven for 20-60 min. Adipocyte and stromal vascular fractions (SVF) were separated by centrifugation, and red blood cells (RBCs) were removed from the SVF by histopaque gradient (Sigma). Single-cell RNA-sequencing libraries were prepared using the MARS-seq pipeline, and sequenced on the MiSeq 500 or HiSeq 2500 Sequencing System (Illumina).

Dataset EGAD00001005100

Competitive selection of somatic mutant clones in normal human skin varies with body site

The risk of getting non-melanoma skin cancer varies over 40-fold across the body. Here we map mutations in normal skin in high and low risk sites in normal donors and those with an increased risk of skin cancer. The density of mutations varied widely, with evidence of positive and negative genetic selection. Regional differences in mutational signatures in high and low cancer risk sites and preferential selection of mutants of TP53 in high risk skin and FAT1 in lower risk skin were observed. 10% of clones had copy number changes in cancer associated genes and the largest had multiple driver mutations with loss of heterozygosity. In hair follicles, a proposed site of origin of skin cancers, mutations in the upper follicle resembled adjacent skin, but the lower follicle was sparsely mutated. We conclude cancer risk reflects the efficiency of transformation of oncogenic mutants rather than the density of mutant clones.

Dataset EGAD00001006194

Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients

Molecular cancer paper (https://doi.org/10.1186/s12943-021-01327-5): This dataset contain shallow whole-genome sequencing (sWGS) of plasma cell-free DNA from cancer patients and healthy subjects, obtained with both Nanopore and Illumina technology. A total of 6 cancer patients and 5 healthy subjects have been sequenced with Nanopore; 4 of the cancer patients have been also sequenced with Illumina. In addition, genomic DNA from white blood cells of one healthy subjects, genomic and 160bp DNA from HEK cells have been sequenced with Nanopore. Genome Biology paper: 3 additional healthy samples have been sequenced (HU), two different bioinformatic pipeline were applied. 2019: Fastqs from the molecular cancer paper were re-demultiplexed and adapter-trimmed (using guppy for multiplex samples, and porechop for singleplex) preserving 5' ends to allow fragmentomics analysis. HAC: All the samples were basecalled with the same updated High Accuracy model (the latest at the time of the analysis) and post-processed as the 2019 dataset. Raw FAST5 are currently available upon request, but will be uploaded soon.

Dataset EGAD00001006888

Glioblastoma stem cell lines RNA-seq (Guilhamon et al.)

RNA was extracted from GSCs using the Qiagen RNeasy Plus kit. RNA sample quality was measured by Qubit (Life Technologies) for concentration and by Agilent Bioanalyzer for RNA integrity. All samples had RIN above 9. Libraries were prepared using the TruSeq Stranded mRNA kit (Illumina). Two hundred nanograms from each sample were purified for polyA tail containing mRNA molecules using poly-T oligo attached magnetic beads, then fragmented post-purification. The cleaved RNA fragments were copied into first strand cDNA using reverse transcriptase and random primers. This is followed by second strand cDNA synthesis using RNase H and DNA Polymerase I. A single “A” base was added and adapter ligated followed by purification and enrichment with PCR to create cDNA libraries. Final cDNA libraries were verified by the Agilent Bioanalyzer for size and concentration quantified by qPCR. All libraries were pooled to a final concentration of 1.8nM, clustered and sequenced on the Illumina NextSeq500 as a pair-end 75 cycle sequencing run using v2 reagents to achieve a minimum of ~40 million reads per sample.

Dataset EGAD00001006813

Single-cell gene expression data from CD8+ T cells from two Austrian COVID19 patients stimulated with wildtype and mutant SARS-Cov-2 peptides

The data contains single-cell gene sequencing data (10x Genomics) from FACS-purified CD8 T lymphocytes from two Austrian patients. The cells were stimulated with one MHC class I peptides obtained from a common (wild type) variant and an emerging mutant variant of the SARS-Cov-2 virus. Then the samples were multiplexed using hashtag oligos. We provide the raw and aligned sequence data for: i. The single-cell experiments ii. The PCR-amplified samples for enrichment of the hashtag oligo multiplexing barcodes iii. The PCR-amplified samples for enrichment of the T Cell Receptor (TCR) VDJ region for immuno-profiling. The samples and libraries were processed and obtained in collaboration between St. Anna Children's Cancer Research Institute (CCRI), CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, and the Medical University of Vienna. The cell barcodes and processed data has been submitted to the GEO database with GEO accession GSE166651.

Dataset EGAD00001006995

Myeloid cell programming in patients with non-medullary thyroid carcinoma

This dataset contains single-cell RNA sequencing data from patients with thyroid cancer (n=7), multinodal Goiter (n=3) and healthy individuals (n=5). Mononuclear cells were taken from both the peripheral blood and the bone marrow compartments. We used a pooled single-cell design where multiple individuals were pooled in a single sample for sequencing (NextSeq 500-V2) and later demultiplexed using their genotype data. Associated metadata contains information on the phenotypes per individual, the pooling design and the linkage between the supplied files and sequenced pools. Due to limitations from EGA in uploading single-cell data, the raw fastq files were processed as follows: (i) I1/I2/R1/R2 fast files were concatenated over the different lanes. (ii) Concatenated I1 and I2 files were interleaved, as were the concatenated R1 and R2 files to generate two fastq files per pool containing all the information. To interleave the fastq files, the BBmap tool bbmap/reformat.sh was used, which can also be used to de-interleave the files.

Dataset EGAD00001008108

Alignment BAM files and gene count files of the Illumina Sequencing Data (10 tumor samples)

Reads were processed with the RNA-seq workflow 1.3.0 developed by the DKFZ Omics IT and Data Management Core Facility (https://github.com/DKFZ-ODCF/RNAseqWorkflow). First, FASTQ reads were aligned via two-pass alignment using STAR 2.5.3a. The STAR index was generated from the 1000 Genomes assembly and GENCODE Version 19 gene models with a sjdbOverhang of 200. Duplicate marking of the resultant main alignment file was done with sambamba 0.6.5. Gene-specific read counting was performed using featureCounts (from Subread 1.5.1) over exon features based on GENCODE Version 19 gene models. Both reads of a paired fragment were used for counting, and the quality threshold was set to 255, indicating that STAR found a unique alignment. Strand-specific counting was also used. For RPKM and TPM calculations, all genes on chromosomes X and Y, the mitochondrial genome, as well as rRNA and tRNA genes were omitted as they are likely to introduce library size estimation biases.

Dataset EGAD00001008969

Upper cortical layer-driven network impairment in schizophrenia - 10x genomics v3 snRNA-seq and Visium spatial transcriptomics datasets

This dataset contains 10x Genomics v3 3’ single nuclei RNA sequencing (24 human schizophrenia and control samples) and 10x Genomics Visium spatial transcriptomics (14 human schizophrenia and control samples) datasets. Files are in .bam format, output of the cellranger v3.1.0 (https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/3.1/using/count) for snRNA-seq and spaceranger v1.1.0 (https://support.10xgenomics.com/spatial-gene-expression/software/pipelines/1.1/using/count) for Visium samples. Reads were mapped against Release 97 of human genome from Ensembl (http://ftp.ensembl.org/pub/release-97/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.primary_assembly.fa.gz http://ftp.ensembl.org/pub/release-97/gtf/homo_sapiens/Homo_sapiens.GRCh38.97.gtf.gz). More details on sample processing are available in the biorXiv pre-print (https://doi.org/10.1101/2020.11.17.386458) and upcoming publication in Science Advances. BAM files can be converted to fastq files using bamtofastq tool (https://support.10xgenomics.com/docs/bamtofastq) with downstream remapping using tools and genomes of choice.

Dataset EGAD00001009173

Single-cell RNA sequencing of airway epithelial cells derived from patient-specific and gene-corrected human iPSCs carrying a CCNO variant

This study aims to elucidate the molecular mechanisms underlying the pathology of Primary Ciliary Dyskinesia (PCD) caused by disease-associated gene variants. To this end, we will establish patient-specific iPSCs and gene-corrected iPSC lines, differentiate them into airway epithelial cells, and perform single-cell RNA sequencing for comparative transcriptomic analysis. Insights gained from this study are expected to contribute to the development of novel diagnostic and therapeutic strategies for PCD. The identifier "J-DS000923" described in the published article corresponds to the dataset deposited in JGA under accession JGAS000846.

Study JGAS000846

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

Substance Dependence GWAS in European- and African - Americans

This study includes SSADDA (Semi Structured Assessment for Drug Dependence and Alcoholism) assessed subjects (mostly unrelated, but including some affected sibling pairs) recruited in the course of several substance dependence genetics projects. The sample includes 1,531 self-reported African-American (AA) subjects, 1,339 self-reported European-American (EA) subjects, and 2 who reported race as "unknown" or "missing".

Study phs000952

Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)

Cohort Description The Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) is a multi-center, observational, longitudinal case-control study designed to guide future development of therapies for COPD. SPIROMICS has recruited 2,983 COPD cases and controls, 40-80 years old with 20+ pack-years of smoking at 12 US sites in 2010–2015.

Study phs002909

Integrating Circulating Tumor DNA Analysis and Radiomics for Dynamic Risk Assessment in Localized Lung Cancer

DNA was isolated from pre-treatment and mid-treatment plasma samples and matched germline samples from patients undergoing chemoradiation therapy for stage IIB-IIIB non-small cell lung cancer. Sequencing libraries were hybrid captured using custom selector pools designed to target genes frequently mutated in non-small cell lung cancer prior to ultra-deep next generation sequencing.

Study phs003947

16802 results for "sec+and+unspecified+malignant+neoplasm"

in 23.31 milliseconds.