15041 results for "cancer studies using rna-seq"

in 40.44 milliseconds.

• Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 1.

  Dataset contains Exome sequencing data (aligned and base quality score recalibrated BAM files) for 236 tumor samples + matched normal from blood, collected from 21 patients with adult diffuse glioma. The majority of these samples were spatially-mapped during sample collection, enabling the genomic information derived from them to be mapped in 3D space.

  Dataset EGAD00001005221

• scRNA-seq dataset to study interactions between HSPCs, BMSCs and immune microenvironment

  Mechanisms of clonal evolution in myeloid neoplasms remain incompletely understood. Darwinian theory predicts that the (micro)environment of clone-propagating stem cells may contribute to clonal selection. Here, we provide data fitting this model, establishing a relationship between stromal niche inflammation, inflammatory stress in HSPCs, clonal resistance and leukemic evolution in human MDS.

  Dataset EGAD00001015770

• Integrative Analysis of Lung Adenocarcinoma in Never Smokers

  We performed whole genome sequencing of lung cancers from never smoker subjects from Institut universitaire de cardiologie et de pneumologie de Québec - Université Laval (IUCPQ-UL) (N=125), Université Côte d'Azur (Nice) (N=47), the Environment And Genetics in Lung cancer Etiology (EAGLE) study (N=27), Yale University (N=22), and Moffitt Cancer Cente (N=11).

  Study phs001697

• Phylogenetic analysis of combined lobular and ductal carcinoma of the breast

  Breast cancer manifests in diverse forms, with particular reference to various cell types harboring different mutations and gene expression profiles. To elucidate the clonal relationship between cancer cells in tumors composed of both ductal and lobular phenotypes, we analyzed two combined lobular and ductal carcinoma (CLDC) cases, including one mixed ductal-lobular carcinoma (MDL) lesion, by next generation sequencing.

  Study JGAS000300

• Somatic_mutation_and_clonal_evolution_in_the_human_bladder_Novaseq

  In this study, we aim to characterise the landscape of mutation and clonal selection in the human bladder. The data in this study will be generated by whole-genome sequencing of laser-dissected microbiopsies from the bladder. The samples utilised in this study will include urothelium from transplant donors with no history of bladder cancer and cystectomy specimens from patients with bladder cancer.

  Study EGAS00001003433

• SDH_deficient_renal_tumours___WGS_

  Succinate dehydrogenase (SDH) deficient renal cancers are a rare and understudied subtype of renal cancer. As such they represent an unmet need in kidney cancer research. Here, we seek to describe the genomics and transcriptomics of SDH deficient renal cancers by sequencing five such tumours. We document their mutational burden, define driver mutations, demonstrate typical patterns of structural variants, and estimate the cell of origin and cellular composition.

  Study EGAS00001004102

• MutWP5: CRUK Mutographs of Cancer: Breast: Cancer Mastectomy (WG) (2020-01-29)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastectomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2020-01-29.

  Dataset EGAD00001005922

• MP2PRT: Evaluation of an Inflammation Polygenic Risk Score (iPRS) to Predict Cancer Related Cognitive Impairment and Fatigue in Patients Receiving Chemotherapy for Non-Metastatic Breast Cancer in URCC0701 and URCC10055

  This study is a secondary analysis of cancer related cognitive impairment (CRCI) and cancer related fatigue (CRF) among participants in URCC0701 and URCC10055 from the University of Rochester NCI Community Oncology Research Program (NCORP) Research Base. CRCI and CRF are common, troublesome, and dose-limiting toxicities reported by patients undergoing breast cancer chemotherapy that have an etiologic basis linked to low-grade systemic inflammation. Chronic, low-grade systemic inflammation is, in part, genetically determined with common single nucleotide polymorphisms (SNPs) capturing variation across individuals. This study aimed to 1) determine whether an inflammation polygenic risk score (iPRS) is associated with CRCI or CRF, 2) determine whether the relationship between the iPRS and CRCI or CRF is modified by exercise at the time of cancer treatment, 3) identify SNPs associated with serum cytokines measured at the time of cancer treatment, and 4) identify novel CRCI- and CRF-associated risk SNPs via genome-wide association analyses. We found that there was a significant inverse correlation between the iPRS and change in fatigue score from pre-chemotherapy to post-chemotherapy while there was no statistically significant association between the iPRS and cognitive impairment score. The inverse relationship between the iPRS and fatigue may be explained in part by the finding that the iPRS was also significantly associated with greater pre-chemotherapy fatigue, suggesting that women with a genetic predisposition to low-grade systemic inflammation (i.e., high iPRS) have more fatigue at the time of breast cancer diagnosis and, therefore, are less likely to worsen over the course of treatment. In contrast, women with a low iPRS had significantly less fatigue pre-chemotherapy and a significant worsening of fatigue from pre- to post-chemotherapy. The relationship between the iPRS and fatigue remained after adjustment for patient and cancer treatment covariates and was most pronounced in women who reported regularly exercising for at least 6 months prior to starting their cancer treatment. Exploratory genome-wide analysis identified a novel risk locus on chromosome chr6q27, tagged by rs9365961, associated with CRCI. This locus is upstream of TBXT, which encodes an embryonic nuclear transcription factor previously associated with susceptibility to neural tube defects. The genome-wide SNP data, patient-reported CRCI and CRF outcome measures, and covariate data used in this analysis are available through dbGaP.

  Study phs003688

• Genetic Analysis of Substance Use Disorder Using the Indiana Biobank Data

  The goal of this study is to identify genes related to substance use disorders. The study participants were selected from the Indiana Biobank. The Indiana Biobank provides centralized processing and storage of specimens that are linked to participants' electronic medical information. Cases were defined as having any type of substance use disorders by using ICD9/10 codes, including alcohol, cannabis, cocaine, opioid, nicotine, and other substances. Controls were defined as not having any type of substance use disorders. The Indiana Biobank is part of the Indiana Clinical and Translational Sciences Institute (CTSI), a state-wide research partnership among Indiana University, Purdue University, and the University of Notre Dame.

  Study phs003025

• Pilot study of adoptive cell therapy using cultured tumor infiltrating lymphocytes for Japanese melanoma patients refractory to immune-checkpoint inhibitors

  To evaluate feasibility of the adoptive cell therapy (ACT) using tumor infiltrating lymphocytes (TIL) in Japanese melanoma patients who failed the immune checkpoint inhibitors (ICIs) and investigate the immune components and immunologic milieu within the pretreatment tumor and expanded TILs from there.?Three patients whose clinical subtype were mucosal, superficial spreading, and acral melanoma were treated and the all completed the TIL-ACT. Clinical response were one short-partial response, one relatively long-stable disease, and one progression disease. Whole-exome and transcriptional analysis of pretreatment tumor revealed the various?immunophenotypes including tumor mutation burden with immunogenic neoantigens and upregulation of immunosuppressive gene signatures.

  Study JGAS000249

• BLUEPRINT Gene expression analysis during human B-cell differentiation using the Affymetrix Human Genome U219 Array

  We performed gene expression analysis using the Affymetrix Human Genome U219 Array of 9 subpopulations covering the complete B-cell maturation program: hematopoietic progenitor cells (HPC); pre-B-I cells (preB1C); pre-B-II cells (preB2C); naive B cells from peripheral blood (naiBC); naive B cells from tonsil (t-naiBC); germinal center B cells (gcBC); plasma cells from tonsil (t-PC); memory B cells from peripheral blood (memBC) and plasma cells from bone marrow (bm-PC). All the samples were isolated from healthy donors and, with the exception of bm-PC (only 1 replicate), we used 3 to 11 biological replicates of each subtype.

  Study EGAS00001001197

• Prediction of DNA Repair Inhibitor Response in Short Term Patient-Derived Ovarian Cancer Organoids

  In this study, 34 ovarian tumor organoids generated from 23 patients underwent paired DNA damage repair defect functional analyses and whole exome sequencing analysis to compare genetic mutational status to DNA repair functional capacity. 22 of the patients had high grade serous cancer and 1 of the patients had low grade serous cancer. A normal control, fresh parent tumor, and cells from the organoid culture generated from the parent tumor underwent whole exome sequencing analysis and the data from the sequencing analysis is provided here.

  Study phs001685

• Intrapatient tumor heterogeneity and clonal evolution in metastatic salivary gland cancer: an autopsy study: access to data

  Funded by the Radboud Oncology Fund and the Dr. C.J. Vaillant Fund, the Salivary Gland Cancer Autopsy research group (Research Group) has sequenced DNA of 17 salivary gland cancer samples of and three healthy control samples from three patients with salivary gland cancer. This research project is led by Carla M.L. van Herpen from Radboud University Medical Centre in Nijmegen, the Netherlands (“Radboudumc”). The DNA sequencing data have been used for an analysis of intrapatient tumor heterogeneity and clonal evolution of metastatic salivary gland cancer. The Research Group is willing to consider applications from third party researchers for access to the DNA sequence data. Access to the data will be granted to qualified researchers for approved use. Access to DNA Sequencing Data is available by application to the Data Access Committee (DAC). Researchers granted access to DNA Sequencing Data must feedback the results of their research to the Research Group, after publication in accordance with the Research Group publication policy set forth in the Data Access Agreement.

  Dac EGAC50000000792

• Circulating tumour DNA abundance and potential utility in de novo metastatic prostate cancer

  Several systemic therapeutic options exist for metastatic castration sensitive prostate cancer (mCSPC). Circulating tumour DNA can profile metastatic castration resistant prostate cancer and influence treatment decisions, but remains untested in mCSPC. We set out to determine ctDNA abundance at de novo mCSPC diagnosis and whether ctDNA provides complementary clinically relevant information to a prostate biopsy. We collected and sequenced 77 plasma cell-free DNA samples from 53 newly diagnosed patients with mCSPC. Targeted sequencing was also performed on DNA from 48 diagnostic prostate tissue samples.

  Study EGAS00001003351

• Anaplastic_Meningioma_WGS_X10

  Anaplastic meningiomas are a rare, malignant variant of meningioma. At present there is no effective treatment for this cancer. The aim of the study is to identify somatic mutations in anaplastic meningiomas. We plan to sequence a set of 500 known cancer genes in 50 anaplastic meningioma and corresponding peripheral blood DNA samples. Bioinformatics will be used to analyse the results to assess the probability of these mutations being causal and so likely of critical importance for the tumour growth. Identification of these mutations will guide selection of appropriate compounds to effectively treat the disease.

  Study EGAS00001000859

• Non-small cell lung cancer proteome subtypes expose targetable oncogenic drivers and immune evasion mechanisms

  Proteome-level data of non-small cell lung cancer remains limited. In this study, we have collected 141 cases, and performed histological review, methylation profiling (113), custom panel sequencing (140), microarray expression profiling (118) and mass-spectrometry based proteomics (141). We identified six distinct groups of patients driven by histology, growth pattern, immune cell infiltration, druggable driver mutations, and hypomethylation-associated neoantigen burden. We validated the subtypes in independent proteomics datasets. Proteomics can refine treatment-oriented subtyping of non-small cell lung cancer.

  Study EGAS00001005482

• MutWP5__CRUK_Mutographs_of_Cancer__Breast__Cancer_Mastectomy__WG_

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastectomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this portion of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers.

  Study EGAS00001003317

• Temporal Dissection of Tumorigenesis in Primary Cancers

  The earliest genetic abnormalities in cancer represent a unique opportunity for timely clinical diagnosis. Classic deep sequencing of tumors identifies many aberrations acquired later in cancer progression. In this study, data regarding simple mutation and chromosomal aberration were integrated to trace the evolution of cutaneous squamous cell carcinomas and ovarian adenocarcinomas. Only after the second allele of TP53 was lost did the genome enter a window of extreme genomic vulnerability, in both cancer types, eventually acquiring more than 100,000 mutations in skin cancers. Inactivating Notch mutations were also identified as prevalent secondary changes. These results add context to the idea of TP53 mutation as dominant negative and occurring later in tumorigenesis.

  Study phs000418

• 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

• The whole blood of female volunteers and sperm from the male volunteer were used to extract genomic DNA to do whole genome sequencing. Distinguished SNPs between parental genomes were retained to analyze parental allele-specific DNA methylation and chromatin accessibility in scCOOL-seq data.

  DNA methylation, chromatin states, and their interrelationships represent critical epigenetic information, but those are largely unknown in human early embryos. Here, we apply scCOOL-seq (Chromatin Overall Omic-scale Landscape Sequencing) to generate a genome-wide map of DNA methylation and chromatin accessibility at single-cell resolution during human preimplantation development. Unlike in mice, the chromatin of paternal genome is already more open than that of maternal genome at the mid-zygote stage in humans, and this state is maintained until the 4-cell stage. After fertilization, genes with high variations in DNA methylation and those with high variations in chromatin accessibility tend to be two different sets. Furthermore, 1,797 (35%) out of 5,155 widely open chromatin regions in promoters closed when transcription activity was inhibited, indicating a feedback mechanism between transcription and open chromatin maintenance. Our work paves the way for dissecting the complex, yet highly coordinated, epigenetic reprogramming during human preimplantation development.

  Study EGAS00001002987

• HCI-PDX Trial Center for Breast Cancer Therapy

  The HCI-PDX Trial Center for Breast Cancer Therapy study is a collection of patient-tumor samples that are serially established as patient-derived tumor xenografts (human tumor in mouse) and matching organoids. For this study, we describe valuable methods and resources to generate organoids and use them as cost-effective models for precision drug screens. This study leveraged whole-exome sequencing, RNAseq, and SNP-array data to illustrate how the heterogeneity of tumors is preserved in xenograft and organoid models. Sequencing files are provided for whole-exome and RNAseq data. Processed copy number variant calls from the SNP arrays are also available. A full description of the study can be found in the article entitled, "A human breast cancer-derived xenograft and organoid platform for drug discovery and precision oncology," written by Guillen et al., 2022 in Nature Cancer (PMID: 35221336).

  Study phs002479

• Childhood Cancer Data Initiative (CCDI): Molecular Characterization Initiative

  The National Cancer Institute's (NCI) Childhood Cancer Data Initiative (CCDI) focuses on the critical need to collect, analyze, and share data to address the burden of cancer in children, adolescents, and young adults (AYAs). The Molecular Characterization Initiative (MCI) will further the CCDI's goals by providing access to better diagnostic tests for pediatric and AYA patients. The molecular characterizations of solid tumors, soft tissue sarcomas, and rare diseases are performed in a CLIA-certified setting as results may be used to screen for and/or confirm clinical trial eligibility, direct treatment, or otherwise contribute to the conduct of the trial. The following molecular characterization assays were performed:Tumor/Normal Whole Exome sequencing Methylation arraysArcher fusion panel Deidentified clinical reportsNote: New data will be added periodically, please check the CCDI Hub Explore site for updates.

  Study phs002790

• Combination_therapies_for_personalized_cancer_medicine

  It is the ambition of the team formed by members of the Netherlands Cancer Institute (NKI) and the Cancer Genome Project at the Wellcome Trust Sanger Institute (WTSI) to unravel the genomic and phenotypic complexity of human cancers in order to identify optimal drug combinations for personalized cancer therapy. Our integrated approach will entail (i) deep sequencing of human tumours and cognate mouse tumours; (ii) drug screens in a 1000+ fully characterized tumour cell line panel; (iii) high-throughput in vitro and in vivo shRNA and cDNA drug resistance and enhancement screens; (iv) computational analysis of the acquired data, leading to significant response predictions; (v) rigorous validation of these predictions in genetically engineered mouse models and patient-derived xenografts. This integrated effort is expected to yield a number of combination therapies and companion-diagnostics biomarkers that will be further explored in our existing clinical trial networks.

  Study EGAS00001000655

• Integrative sequencing reveals alterations in untreated and castration resistant prostate cancer

  We report the integrative sequencing of genomic, transcriptomic and DNA methylation changes in 28 untreated (PC) and 13 castration resistant prostate cancers (CRPC). AR, TGF-β and WNT signaling pathways were altered in CRPCs. We identified two new fusion genes, TMPRSS2-SKIL and DOT1L-HES6. Fusion analysis in an independent cohort validated SKIL as a recurrent 3’ fusion partner and oncogene in prostate cancer. The HES6 fusion was found in an AR-negative CRPC, and HES6 overexpression in vitro led to androgen independent growth. A distinct DNA methylation signature was found for CRPC. Transcriptome assembly uncovered 128 previously unannotated prostate cancer associated transcripts, including the ERG regulated transcript TPCAT-10-36067 whose knockdown had a dramatic effect on the growth, invasiveness, and rate of apoptosis of prostate cancer cells.

  Study EGAS00001000526

• Digital tEchnology For Lung Cancer Treatment

  The aim of the DEFLeCT project (Digital tEchnology For Lung Cancer Treatment) is to generate a technological platform for precision medicine in order to set predictive personalised algorithms for patient diagnosis and therapy. All resectable patients having histologically confirmed stage IB-IIIA non-small cell lung cancer(NSCLC) will be enrolled in the PROMOLE study, a related and ongoing observational prospective clinical study, for tissue sampling. A large biobank of lung cancer samples and the corresponding healthy tissues and biological components (ie, blood, stools, etc.) with complete clinical, pathological and molecular information will be collected. The project will lay the basis of a knowledge hub and qualified technology aimed not only at answering the medical and scientific community's questions, but also meant to be useful to individual patients by predicting the response to adjuvant and second-line drugs in case of relapse of the disease.

  Study EGAS00001007219

• EGAD00010000768

  Replication data for HipSci normal samples using both HumanCoreExome-12_v1 and HumanOmni2.5-8 BeadChips

  Dataset EGAD00010000768

• Helleday_HRAS Project

  This experiment is looking at the mutational signatures generated by engineered HRAS mutations by using whole genome sequence generated on massively parallel next generation sequencers.

  Dataset EGAD00001000302

• Yemen_Somali.Omni5

  The individuals were assayed for genome-wide SNP genotypes using the Illumina Human Omni5 Bead Chip (Illumina), which surveys 4,284,426 single nucleotide markers regularly spaced across the genome

  Dataset EGAD00010001651

• KuwaitPopGenetics

  Genome-wide Genotyping of 620 Arab individuals using Illumina iSelect platform with HumanOmniExpress bead chips

  Dataset EGAD00010002063

• MethylationEPIC_850K

  This dataset includes IDAT files from 160 samples (57 primary prostate cancers, 95 proste-derived brain metastases, and 7 normal tissues). The samples were profiled using the Illumina Infinium MethylationEPIC BeadChips (850K)

  Dataset EGAD00010002372

• ctDNA raw data (BAMs)

  Raw data of ctDNA profiling using the PredicineWES+ or PredicineBEACON assay in patients enrolled in divarasib phase I GO42144 study.

  Dataset EGAD50000000530

• WGS

  Our cohort represents infants with ALL in whom KMT2Ar was not detected by FISH or by standard cytogenetics. Whole-genome sequencing (WGS) was performed using Illumina’s HiSeqX to a depth of >30X.

  Dataset EGAD50000000594

• WGS data of multiple myeloma

  Dataset containing WGS data from 4 patients with 17 samples with multiple myeloma. The sequencing was always paired and performed using Illumina NovaSeq 6000

  Dataset EGAD50000000437

• GCAT| SNParray coreSpain V3 TopMed

  4988 samples issued from GCAT cohort, genotyped with MEGAex-Infinium Array, with data for Cr1-23. Plink files with QC and imputed using TOPMed r2.

  Dataset EGAD00010002749

• Methylation profiling of CDS and ES tumor samples

  Methylation profiling of 9 CDS and ES tumor samples, using the approach described in "Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target

  Dataset EGAD00010002760

• Single Cell-Derived chemoradiotherapy-treated colonies.

  60X WGS of single cell-derived colonies of DHL4 cells treated with platinum or RT (or unexposed control). 16 bam files aligned using MGP1000 pipeline (GRCh38).

  Dataset EGAD50000001461

• GCAT| SNParray GSA TopMed

  2746 samples issued from GCAT cohort, genotyped with GSA Array, with data for Cr1-23. Plink files with QC and imputed using TOPMed.

  Dataset EGAD00010002758

• WES of Multiple myeloma/MGUS cases (germline) - Fastq files

  WXS - Exome capture using the Twist Human Core Exome Kit on germline DNA, paired-end (2x100bp) sequencing on a NovaSeq system. Number of samples: 295

  Dataset EGAD50000001799

• HICHIP_TALL_t_14_16_translocation

  For patient P01, HiChIP experiment for was performed using the Arima-HiC+ kit (A510008, Arima genomics) according to the manufacturer’s protocols.

  Dataset EGAD50000002167

• Whole genome sequencing of chronic lymphocytic leukemia

  Whole genome sequencing of chronic lymphocytic leukemia, 49 CLL/control pairs, sequenced on HiSeq X Ten with DNA prepared using Illumina TruSeq DNA Nano.

  Dataset EGAD00001009638

• Somatic MT SNV calls

  Filtered somatic MT SNV (heteroplasmy) calls detected using mitoCaller (v1.0)

  Dataset EGAD00001007871

• Cell line sequencing data

  SmMIP libraries using bulk cell line DNA and DNA mixes were generated in replicates and were sequenced on the NovaSeq SP platform (Illumina)

  Dataset EGAD00001007790

• Mucoepidermoid Carcinoma

  Whole exome sequencing data for 18 mucoepidermoid carcinoma samples. The samples were used for Illumina TruSeq library construction and captured using Agilent V4 exome panel. The PE fastq files are provided.

  Dataset EGAD00001003958

• Live slow-frozen human tumor tissues scRNA

  Bam files of 17 samples from 11 different patients. The scRNAseq data were obtained using the 10X 3' Gene Expression kit.

  Dataset EGAD00001009284

• Mucoepidermoid carcinoma- normals

  Whole exome sequencing data for 18 mucoepidermoid carcinoma samples. The samples were used for Illumina TruSeq library construction and captured using Agilent V4 exome panel. The PE fastq files are provided.

  Dataset EGAD00001004946

• Endometriosis

  Whole exome sequencing data for matched normal and endometriosis samples. Samples were prepared using Agilent Sureselect capture kit, and sequenced on an Illumina HiSeq 2500. The submitted files are in BAM format.

  Dataset EGAD00001004964

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• 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

• Association of DNA-methylation profiles with immune responses in breast cancer patients

  Genome-wide DNA methylation profiling of genomic DNA isolated from blood PBMCs of breat cancer patients before the start of therapy.

  Dataset EGAD00010001854

• INVADE bulk RNAseq

  Fastq files of bulk RNAseq data from DCIS, invasive and microinvasive breast cancer at diagnosis. This dataset covers 18 DCIS cases, 17 microinvasive and 20 primary invasive breast cancer.

  Dataset EGAD50000000320

• RNAseq analysis on metastatic Colorectal Cancer xenografts samples

  Bank of metastatic colorectal cancer (mCRC) of Patient Derived Xenografts (PDXs)

  Dataset EGAD00001009171

• Whole Exome Sequencing of Localized Prostate Cancer Patients

  Whole exome sequencing of localized prostate cancer patients in this study contained pair tumor-normal samples and validated tumor content.

  Dataset EGAD00001008274

• Germline WES data of pediatric cancer patients

  This dataset includes bam files (aligned to hg38) from the germline of pediatric cancer patients.

  Dataset EGAD00001008763

• Targeted analysis of chondrosarcoma cancer genes (2019-04-01)

  Targeted analysis of chondrosarcoma cancer genes . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004877

• Bulk tumor RNAseq of bladder cancer patients

  RNAseq fastq files from 611 bulk pre-treatment tumors from two indications: metastatic urothelial bladder cancer patients (IMvigor210) and metastatic renal cell carcinoma (IMmotion150)

  Dataset EGAD00001006960

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

  Geographic and age-related variations in mutational processes in colorectal cancer - patient metadata files (Mutographs)

  Dataset EGAD00001015437

• Colorectal organoids and tumoroids - pulldown

  Targeted capture of cancer gene panel bait set in single cell derived organoids from colon tissue and colorectal cancer from 1 patient.

  Dataset EGAD00001001208

• Transcriptome of biliary tract cancer

  Fastq files of RNAseq of 182 samples of biliary tract cancer

  Dataset EGAD00001001693

• Ovarian cancer organoid biobank - followup

  WGS of more samples in the ovarian cancer organoid biobank dataset.

  Dataset EGAD00001005707

• The complexity of tobacco smoke induced mutagenesis in head and neck cancer - sequence data (Mutographs)

  The complexity of tobacco smoke induced mutagenesis in head and neck cancer - sequence data (Mutographs)

  Dataset EGAD00001015386

• Geographic and age-related variations in mutational processes in colorectal cancer - copy number variants (Mutographs)

  Geographic and age-related variations in mutational processes in colorectal cancer - copy number variants (Mutographs)

  Dataset EGAD00001015487

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Autism - Simons Simplex Collection (SSC)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001676

• Strabismus, CCDD and other anomalies

  Strabismus is one of the most common ophthalmological diseases affecting our population. It has many detrimental effects for affected individuals, including functional visual loss from amblyopia, secondary psychosocial difficulties, and limited employment opportunities. Strabismus also imposes a significant economical burden on society from the cost of screening programs, surgical correction, and lost productivity. Congenital incomitant strabismus is a broad term that encompasses congenital ocular motility disorders with restricted movement in one or more directions of gaze, and includes various forms of Duane's retraction syndrome, horizontal gaze palsy, congenital fibrosis of extraocular muscles, and Moebius syndrome. Incomitant strabismus together with a group of related disorders such as congenital ptosis and congenital facial palsy have been collectively redefined as congenital cranial dysinnervation disorders (CCDDs). This redefinition stemmed from previous studies in the Engle lab showing that these disorders can be caused by mutations in genes encoding transcription factors critical to ocular cranial motor neuron development and by genes that encode proteins essential to the proper growth and guidance of developing axons. Thus, while these disorders account for only a small percent of strabismus, understanding their genetic etiology has led to our ability to provide genetic testing and counseling, and has provided the first insights into the molecular etiologies of strabismus. While the Engle lab has identified all seven CCDD genes published to date, our cohort still includes >100 familial CCDD pedigrees that are mutation-negative. We continue to utilize co-segregation analysis and whole exome or whole genome sequencing technologies to identify new disease genes in this mutation-negative cohort.

  Study phs000478

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: SPARK Simons Foundation Powering Autism Research for Knowledge

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal.An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002511

• VCRC - Giant Cell Arteritis Longitudinal Study

  The development and validation of accurate biological markers and predictors of disease activity and outcome for Giant Cell Arteritis, a form of idiopathic vasculitis, would have a major positive impact on the clinical care of patients with this rare disease, be an important insight into the design of clinical trials and feasibility of new drug development, and provide important insight into the pathogenesis of this condition. Current measures of disease activity, including erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP), while helpful in selected settings, are mostly considered highly flawed and markers whose poor correlation with disease flares makes them inadequate to help guide therapy. Similarly, ESR and CRP are clearly unhelpful as diagnostic tests for vasculitis. The current state of clinical investigation for vasculitis relies heavily upon determination of disease status solely by clinical presentation and investigator opinion. Thus, discovery and validation of more precise markers that quantifiably measure activity, predict disease course, and correlate with an important biological process, would be of great importance. Knowledge to be gained from this study could potentially be highly important. Discovery of effective biomarkers of vasculitis and assessment of long term disease course and complications by the collection of clinical and diagnostic imaging studies proposed could lead to better care and less toxic treatment regimens. Furthermore, insight into the pathophysiology of vasculitis could be gained and this might lead to better treatments and improved outcomes in terms of reduction of vascular and treatment related complications. Ideally, excellent biomarkers reflect a sophisticated understanding of the pathophysiology of a disease.

  Study phs000588

• National Eye Institute (NEI) Primary Open-Angle African American Glaucoma Genetics (POAAGG) Study

  The purpose of the POAAGG study is to investigate the genetic architecture of primary open-angle glaucoma (POAG) in African Americans. This population is up to eight times more likely to develop glaucoma than non-Hispanic whites, yet no large-scale genetics studies have specifically addressed this ethnic group. The POAAGG study aims to enroll 7765 patients, consisting of a discovery cohort of 5500 subjects (2000 cases and 3500 controls) and a validation cohort of 2265 subjects (1000 cases and 1265 controls). The study population consists of self-identified blacks (African Americans, African descent, or African Caribbean), 35 years or older, identified from the Philadelphia region. Subjects are recruited from the Scheie Eye Institute and its research sites in Philadelphia, PA, as well as from the Penn Medicine Biobank. Fellowship-trained glaucoma specialists classify each subject as a case, control, or glaucoma suspect based on specified criteria. As of 02/01/2017, a total of 8187 subjects have been recruited to the POAAGG study, including 2522 cases, 4545 controls, and 1120 suspects. A comprehensive genetic analysis of POAG, including a genome-wide association analysis, is currently underway. The GWAS was conducted on the Illumina Infinium Multi Ethnic Genotyping Array (MEGA), which contained custom content tailored to POAG and African Americans. A comprehensive genetic analysis of quantitative traits associated with POAG is also in progress. Over 90% of cases have full phenotypic information, including intraocular pressure, cup-to-disc ratio, central corneal thickness, retinal nerve fiber layer thickness, visual acuity, and visual fields.

  Study phs001312

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Victorian Collaborative AuTism Study (CATS): Family and Community Study of the Genetics of Autism Spectrum Disorder

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002044

• Rare Diseases Clinical Research Network (RDCRN) Vasculitis Clinical Research Consortium (VCRC) Longitudinal Protocol for Polyarteritis Nodosa

  The development and validation of accurate biological markers and predictors of disease activity and outcome in Polyarteritis Nodosa (PAN), a form a idiopathic vasculitis, would have a major positive impact on the clinical care of patients with this rare disease, be an important advance in the design of clinical trials and feasibility of new drug development, and provide important insight into the pathogenesis of this condition. Current measures of disease activity, including erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP), while helpful in selected settings, are mostly considered highly flawed and markers whose poor correlation with disease flares makes them inadequate to help guide therapy. Similarly, ESR and CRP are clearly unhelpful as diagnostic tests for vasculitis. The current state of clinical investigation for vasculitis relies heavily upon determination of disease status solely by clinical presentation and investigator opinion. Thus, discovery and validation of more precise markers that quantifiably measure activity, predict disease course, and correlate with an important biological process, would be of great importance. Knowledge to be gained from this study could potentially be highly important. Discovery of effective biomarkers of vasculitis and assessment of long term disease course and complications by the collection of clinical and diagnostic imaging studies proposed could lead to better care and less toxic treatment regimens. Furthermore, insight into the pathophysiology of vasculitis could be gained and this might lead to better treatments and improved outcomes in terms of reduction of vascular and treatment related complications. Ideally, excellent biomarkers reflect a sophisticated understanding of the pathophysiology of a disease.

  Study phs000590

• Study on the Genetics of Alcoholism (COGA): Smoke Screen and Exome Sequencing

  This is a family study of alcoholism, in which the subjects have been drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), a large, ongoing family-based study that includes subjects from seven sites around the US. COGA has gathered detailed, standardized data on study participants, including diagnostic and neurophysiological assessments. This project has already proved successful in identifying several genes that influence the risk for alcoholism and neurophysiological endophenotypes, which have been independently replicated. COGA data were included as part of two Genetic Analysis Workshops, and the phenotypes are familiar to the genetics community. Alcoholic probands were recruited from treatment facilities, assessed by personal interview, and after securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through an alcoholic proband. Assessment involved a detailed personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Many participants also came to the laboratories for electroencephalographic studies. Neurophysiological features that have been shown to be useful endophenotypes for which we have linkage and in some cases association results are included on a subset of the case-control sample: the beta power of the resting electroencephalogram (EEG), the P3(00) amplitude of the visual event-related potential (ERP), and the theta and delta event-related oscillations (EROs) underlying the P3.

  Study phs001208

• Exome sequencing of uterine leiomyosarcomas

  Uterine leiomyosarcomas (ULMSs) are aggressive smooth muscle tumors associated with poor clinical outcome. Despite previous cytogenetic and molecular studies, their molecular background has remained elusive. To examine somatic variation in ULMS, we performed exome sequencing on 19 tumors. Altogether 43 genes were mutated in at least two ULMSs. Most frequently mutated genes included tumor protein P53 (TP53; 6/19; 33%), alpha thalassemia/mental retardation syndrome X-linked (ATRX; 5/19; 26%), and mediator complex subunit 12 (MED12; 4/19; 21%). Unlike ATRX mutations, both TP53 and MED12 alterations have repeatedly been associated with ULMSs. All the observed ATRX alterations were either nonsense or frameshift mutations. ATRX protein levels were reliably analyzed by immunohistochemistry in altogether 44 ULMSs, and the majority of tumors (23/44; 52%) showed clearly reduced expression. Loss of ATRX expression has been associated with alternative lengthening of telomeres (ALT), and thus the telomere length was analyzed with telomere-specific fluorescence in situ hybridization. The ALT phenotype was confirmed in all ULMSs showing diminished ATRX expression. Exome data also revealed one nonsense mutation in death-domain associated protein (DAXX), another gene previously associated with ALT, and the tumor showed ALT positivity. Aberrant expression of both TP53 and ATRX were associated with poor overall survival. In conclusion, exome sequencing revealed that TP53, ATRX, and MED12 are frequently mutated in ULMSs. ALT phenotype was commonly seen in tumors, indicating that ATR inhibitors, which were recently suggested as possible new drugs for ATRX-deficient tumors, could provide a potential novel therapeutic option for ULMS.

  Study EGAS00001001612

• DNA methylation and the adverse metabolic outcomes of adiposity

  Overweight and obesity affect ~1.5 billion people worldwide, and are major risk factors for type-2 diabetes (T2D), cardiovascular disease and related metabolic and inflammatory disturbances.1,2 Although the mechanisms linking adiposity to its clinical sequelae are poorly understood, recent studies suggest that adiposity may influence DNA methylation,3-6 a key regulator of gene expression and molecular phenotype.7 Here we use epigenome-wide association to show that body mass index (BMI, a key measure of adiposity) is associated with widespread changes in DNA methylation (187 genetic loci at P<1x10-7, range P=9.2x10-8 to 6.0x10-46; N=10,261 samples). Genetic association analyses demonstrate that the alterations in DNA methylation are predominantly the consequence of adiposity, rather than the cause. We find the methylation loci are enriched for functional genomic features in multiple tissues (P<0.05), and show that sentinel methylation markers identify gene expression signatures at 38 loci (P<9.0x10-6, range P=5.5x10-6 to 6.1x10-35, N=1,785 samples). The methylation loci identified highlight genes involved in lipid and lipoprotein metabolism, substrate transport, and inflammatory pathways. Finally, we show that the disturbances in DNA methylation predict future type-2 diabetes (relative risk per 1SD increase in Methylation Risk Score: 2.3 [2.07-2.56]; P=1.1x10-54). Our results provide new insights into the biologic pathways influenced by adiposity, and may enable development of new strategies for prediction and prevention of type-2 diabetes and other adverse clinical consequences of obesity.

  Study EGAS00001001922

• UK10K NEURO ASD SKUSE

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. This sample set of UK origin consists of clinically identified subjects with Autism Spectrum Disorders, mostly without intellectual disability (ie. Verbal IQs >70). The subjects represent children and adults with Autism, Asperger syndrome or Atypical Autism, identified according to standardized research criteria (ADI-algorithm, ADOS). A minority has identified comorbid neurodevelopmental disorders (e.g. ADHD). Family histories are available, with measures of broader phenotype in first-degree relatives.For further information on this cohort please contact David Skuse (d.skuse@ucl.ac.uk).

  Study EGAS00001000114

• UK10K_NEURO_MUIR

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches.The sample selection consists of subjects with schizophrenia (SZ), autism, or other psychoses all with mental retardation (learning disability). The samples were initially collected under the leadership of Walter J Muir (deceased), now with Prof. Blackwood, Dr McKechanie and Prof McIntosh as custodians. These subjects represent the intersection of severe forms of neurodevelopmental disorders, appear to have a higher rate of familiality of SZ than typical, and are likely to have more serious and penetrant forms of mutations.For further information on this cohort please contact Andrew McIntosh (andrew.mcintosh@ed.ac.uk).

  Study EGAS00001000122

• Associations between APOE status and cognitive ability across the lifecourse

  The association between APOE genotype and cognitive function suggests a positive role for the e2 allele and a negative role for the e4 allele. Both alleles have relatively low frequencies in the general population, hence meta-analyses have been based on many small, heterogeneous studies. Here we report the APOE-cognition associations in the largest single analysis to date. APOE status and cognitive ability were measured in 18,337 participants from the Generation Scotland study between 2006 and 2011. The age range was 18-94 years with a mean of 47 (SD 15). Four cognitive domains were assessed: verbal declarative memory (paragraph recall), processing speed (digit symbol substitution), verbal fluency (phonemic verbal fluency), and vocabulary (Mill Hill synonyms). Linear regression was used to assess the associations between APOE genetic status and cognition. Possession of the e4 allele was associated with lower scores on the measures of memory and processing speed in subjects aged >60. Across all age ranges, the e4 allele was linked to better verbal fluency scores. In younger subjects (≤60 years) the e4 allele was linked to higher vocabulary scores. There were no associations between the e2 allele and cognitive ability. As seen in previous meta-analyses, the APOE e4 allele is linked to poorer cognitive performance in the domains of memory and processing speed. By contrast, positive associations were seen between the e4 allele and measures of verbal fluency and vocabulary. All associations were relatively small and, in many cases, nominally significant despite the very large sample size.

  Study EGAS00001001235

• UK10K_RARE_THYROID

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches.Two cohorts of subjects are being analysed: Individuals with Congenital Hypothyroidism (CH) due either to dysgenesis or dyshormonogenesis; Patients with Resistance to Thyroid hormone (RTH), a disorder characterized by elevated thyroid hormones and variable tissue refractoriness to hormone action. The CH cohort has been enriched for genetic aetiologies by recruiting cases that are familial, on a consanguineous background or syndromic. The RTH cohort consists of cases in which candidate gene analyses have been negative.For further information with regard to this cohort please contact Krishna Chatterjee (kkc1@medschl.cam.ac.uk).

  Study EGAS00001000131

• Epigenome-wide methylation analysis of colorectal carcinoma, adenoma and normal tissue reveals novel biomarkers addressing unmet clinical needs

  Studies about CRC biomarker discovery have focused on methylation patterns in normal and colorectal tumor tissue, leading to a lack of knowledge of methylation in adenomas. Therefore, we performed the first epigenome-wide study to compare the epigenomes of all three tissue types combined, and to identify discriminatory biomarkers. Public Illumina MethylEPIC® data was collected from 552 normal, 118 carcinoma and 116 adenoma samples. Pairwise analyses were performed for discovery of differentially methylated probes (DMPs). We identified 693 813, 620 643 and 558 897 DMPs when comparing normal vs carcinoma, normal vs adenoma and adenoma vs carcinoma respectively. To double evidence (DE) these DMPs, analysis of Illumina 450K data from public datasets was performed. Through this analysis, 13 DE DMPs with │Δβ│≥0.3 were identified for adenoma vs carcinoma. A binary logistic regression model was generated to evaluate the discriminatory potential of these DE DMPS. The model was validated in an in-house experimental methylation dataset of 13 adenoma and 9 carcinoma samples. Our classifier reached a cross-validated AUC of 0.996 and 0.855 in the discovery and validation datasets respectively. A sensitivity and specificity of 96% and 95% were reached, with an overall accuracy of 96%. Our analysis show that methylation biomarkers have the potential to discriminate between normal, precursor and carcinoma tissues of the colorectum. More importantly, we highlight the power of the methylome, showing that DMPs can be used as biomarkers in the clinic to identify colorectal adenoma and carcinoma. 

  Study EGAS00001007017

• Study assessing the efficacy and safety of durvalumab plus olaparib plus fulvestrant in selected metastatic or locally advanced ER-positive, HER2-negative breast cancer patients.

  This study aims to evaluate the efficacy of the combination of olaparib, durvalumab, and fulvestrant for the treatment of patients with ER-positive, HER2-negative, locally advanced or metastatic breast cancer with BRCA gene alterations or alterations of genes involved in HRR or MSI status, in terms of the progression-free survival rate (PFSR) at 24 weeks.

  Study EGAS50000001166

• SDH_deficient_renal_tumours___RNA_

  Succinate dehydrogenase (SDH) deficient renal cancers are a rare and understudied subtype of renal cancer. As such they represent an unmet need in kidney cancer research. Here, we seek to describe the genomics and transcriptomics of SDH deficient renal cancers by sequencing five such tumours. We document their mutational burden, define driver mutations, demonstrate typical patterns of structural variants, and estimate the cell of origin and cellular composition.

  Study EGAS00001004103

• Spontaneous mutations in the single TTN gene represent high tumor mutation burden

  Tumor mutation burden (TMB) is an emerging biomarker, whose calculation requires targeted sequencing of many genes. We investigated if the measurement of mutation counts within a single gene is representative of TMB. Whole exome sequencing (WES) data from the pan-cancer cohort (n=10,224) of TCGA, and targeted sequencing (tNGS) and TTN gene sequencing from 24 colorectal cancer samples (AMC cohort) were analyzed.

  Study EGAS00001004009

• Sequence data from stage I of the CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer

  The dataset for the study "Early ctDNA molecular response captures therapeutic response in the first stage of CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer", includes 134 bam files from hybrid capture targeted error-correction next-generation sequencing (PGDx Elio plasma resolve) from plasma cell-free DNA and matched white blood cell DNA from 35 individuals with non-small cell lung cancer on the BR.36 trial, alongside 11 bam files from targeted next generation sequencing (PGDx Elio tissue complete) of tumor DNA from 11 individuals with non-small cell lung cancer on the BR.36 trial.

  Dataset EGAD00001011359

• 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