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• VALCAP files for Ma et al. (2019) SCMC Hybrid

  VALCAP files for Ma et al. (2019) Genome Biology (accepted) titled “Analysis of error profiles in deep next-generation sequencing data"

  Dataset EGAD00001004595

• McGill EMC Release 4 in tissue "fat pad" for cell type "fat cell"

  McGill EMC Release 4 in tissue "fat pad" for cell type "fat cell"

  Dataset EGAD00001001277

• McGill EMC Release 4 in tissue "venous blood" for cell type "T cell"

  McGill EMC Release 4 in tissue "venous blood" for cell type "T cell"

  Dataset EGAD00001001283

• RNAseq files for CHEN WTPDX RNASEQ

  RNAseq files for CHEN WTPDX RNASEQ paper titled "Forty-Five patient-derived xenografts capture the clinical and biological heterogeneity of Wilms tumor"

  Dataset EGAD00001004507

• WES files for Newman MAP3K8 melanoma

  WES files for Newman MAP3K8 melanoma paper titled "Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas"

  Dataset EGAD00001004566

• WGS files for Newman MAP3K8 melanoma

  WGS files for Newman MAP3K8 melanoma paper titled "Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas"

  Dataset EGAD00001004579

• Dataset for "Genome-wide analysis of HPV integration in human cancers reveals recurrent, focal genomic instability"

  Dataset for "Genome-wide analysis of HPV integration in human cancers reveals recurrent, focal genomic instability"

  Dataset EGAD00001000691

• Orthogonal proteogenomic analysis identifies the druggable PA2G4-MYC axis in 3q26 AML

  Our aim was to identify regulators of the EVI1/MECOM gene, which is the most lethal oncogenic TF and is highly expressed in AML with chromosome 3q26 abnormalities.

  Study EGAS50000000347

• Control human putamen and Substantia Nigra

  The study is affiliated to the UKBEC sample of healthy human putamen and substantia nigra phenotype. The gender is from both male and female samples of the the phenotype.

  Study EGAS00001003065

• Mesothelioma_Whole_Genomes

  Genomic architecture of mesothelioma parent study is project 925. This project is set up in parallel to project 925 in order to Whole genome sequence ten of the 59 tumours in that project.

  Study EGAS00001000830

• Genome-wide Association Study of Myasthenia Gravis

  The purpose of this project was to conduct a genome-wide associate study to search for the genetic factors that predispose to myasthenia gravis. The rationale for this study lies in the fact that, although the immunological and physiological processes affecting the neuromuscular junctions of myasthenia gravis patients are well understood, the spectrum of genetic factors that predispose to myasthenia gravis and influence its disease manifestations are not well known. Identification of the myasthenia gravis-related genes will shed light on the fundamental cellular events underlying myasthenia gravis, and will provide focus for research aimed at developing therapies that alter the natural course of the disease. A consortium of fourteen institutions in North America collected DNA samples from 1028 people diagnosed with autoimmune myasthenia gravis. Relevant clinical data have been collected for each patient, including age of onset, severity of disease, response to drug therapy, personal and family history of other autoimmune diseases. Genotyping of the case cohort was performed in the Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD. Genotyping of the case cohort was performed using the HumanOmniExpress-12v1_C SNP array manufactured by Illumina Inc. For the control cohort, we downloaded genotype data from dbGAP (accession phs000196.v2.p1) for 1,998 US neurologically normal individuals. The control cohort had been previously genotyped at the Center for Inherited Disease Research at Johns Hopkins University on HumanOmni1-Quad version 1.0B beadchips (Illumina) as part of the NeuroGenetics Research Consortium GWAS of Parkinson's disease. Analyses were confined to the 677,673 autosomal SNPs that were common to both chips. Of the 1028 samples which were genotyped, 21 samples were excluded due to mismatched genders, 9 were excluded due to low genotype call rate, 5 samples were excluded as duplicates, and 25 samples were excluded as ethnic outliers. The remaining 972 samples were used in analysis.

  Study phs000726

• OurHealth - Cardiovascular Disease in South Asians

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

  Study phs003821

• Utlizing the RA signature to predict response to TNFi

  This study involves bulk RNA-seq analyses of blood cells from patients with rheumatoid arthritis who have had an inadequate response to methotrexate, collected before and 12 weeks after effective treatment with either etanercept or adalimumab. Peripheral blood mononuclear cells were stimulated with anti-CD3 for 24 hours and sorted into CD4+, CD19+, and CD4-CD19- (DN) populations for bulk RNA-seq.

  Study phs002562

• ICARUS-LUNG01 dataset

  A total of 46 frozen tumor biopsies underwent WES analysis, while 41 blood samples were used as germline controls.Tumor samples qualified for whole exome sequencing (WES) if they contained ≥10% tumor cells. For bulk RNA-seq, 20 paired baseline and on-treatment frozen tumor biopsies were analyzed. Tumor samples qualified if they contained ≥30% tumor cells. For GeoMx spatial transcriptomic study we used 7 patients from the ICARUS LUNG01 trial focusing on tumour and immune cell compartments. We selected 7 paired baseline and on-treatment patient samples for analysis. We selected up to 4 regions of interest (ROI) per sample tissue. We identified tumour and immune cell areas of illumination (AOI) using CK and CD45 antibodies respectively

  Dataset EGAD50000001014

• The landscape of somatic mutations in epigenetic regulators across 1000 pediatric cancer genomes

  To define the frequency and pattern of somatic mutations in epigenetic regulators in pediatric cancer, we sequenced 633 genes, encoding the majority of proteins involved in patterning the epigenome, in 1000 pediatric tumors spanning 21 different cancer subtypes. This analysis establishes an epigenetic landscape of pediatric cancer, which expands the knowledge for potential therapeutic targets and for developing personalized therapy.

  Study EGAS00001000449

• Subclonal evolution of four ER+ breast cancers determined by WGS and scRNA-Seq

  We analyzed the subclonal evolution of four ER+ breast cancers over 2-15 years using whole-genome sequencing (WGS) and single-cell RNA-Seq (scRNA-Seq). For each patient we analyzed 2-6 cancer samples, generally metastatic pleural effusions or ascites, by WGS, along with germline DNA. Two of the samples per patient were selected for single-cell RNA-Seq.

  Study EGAS00001002436

• Ancient nuclear genomes enable repatriation of Indigenous human remains

  For many decades Indigenous people, including Native Americans and Aboriginal Australians, have fought for their return of their ancient people. By sequencing ten ancient nuclear genomes of Aboriginal Australians and 27 mitogenomes from ancient pre-European Aboriginal Australians (up to 1,540 yr BP) of known provenance we demonstrate the feasibility of successfully identifying the geographic origins of unprovenanced ancestral remains using genomic methods.

  Study EGAS00001003359

• Test_of_PCR_library_method_on_whole_genmoe_samples

  We will sequence 2 whole genome pairs which have had the libraries prepared with a PCR step. The resulting sequence will be compared to teh same samples which have had sequence obtain using a no_PCR library method. the sequence obtained in this experiment may or may not be used in conjunction with the other sequence obtain for these samples in the search for novel cancer mutations.

  Study EGAS00001000214

• November 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  November 2020 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001007529

• HV31 - Read identifier list for local CCS, CLR, ONT and MGI reads

  This file contains read identifiers for local CCS, CLR, ONT and MGI reads for each of the eight selected genomic regions (HLA, KIR, IGH, IGK, IGL, TRA, TRD, andTRG). We extracted these reads by aligning whole-genome sequencing data to a draft whole-genome de novo assembly, and selecting reads that map to contigs representing each region. These reads were involved in the polishing and validation of the HV31 assembly. Please refer to the relevant manuscript (https://doi.org/10.1101/2021.02.03.429586) for additional details. Read identifiers are stored in JSON format. Along with the full FASTQ files, this file enables convenient re-analysis of the HV31 sequencing data in the eight selected regions.

  Dataset EGAD00001007761

• Chromatin accessibility (ATAC-seq) and transcriptome (RNA-seq) data from immune cells for healthy young and healthy old subjects

  Dataset consisting of: (1) N=234 genome-wide chromatin accessibility (ATAC-seq) profiles for distinct N=21 healthy old and N=28 healthy young subjects. ATAC-seq biological samples provided for the following tissues: PBMC (N=24), CD14+ monocytes (N=18), CD8+ memory T cells (N=7), CD8+ naive T cells (N=7), CD4+ memory T cells (N=7), CD4+ naive T cells (N=7), and naive B cells (N=7). (2) N=39 genome-wide transcription (RNA-seq) data for distinct N=15 healthy old and N=24 healthy young subjects' PBMCs.

  Dataset EGAD00001003602

• Assessment of RNA-Seq Sample Preparation Methodology

  The goal of this study was two-fold, to determine if common purification techniques have any effect on downstream differential expression analysis and to evaluate combinations of alignment and differential expression software for reliability. To this end, blood was collected from three individuals and pooled during and after extraction. After pooling and mixing was completed, samples were divided into three aliquots for testing. The first aliquot was a control and not purified or concentrated. It was diluted to produce samples of varying concentrations for testing. The second aliquot was diluted to 20 ng/μL and used to test six different variations on the AMPure XP bead purification procedure. The last aliquot was also diluted to varying concentrations of 60, 30, and 9.6 ng/μL and purified using MinElute columns. Samples were submitted for total RNA-Seq library preparation and sequencing. Library preparation was performed using the TruSeq Stranded Total RNA with Ribo-Zero Globin kit (20020612, Illumina Inc.), and 2x150 bp PE sequencing was done on an Illumina NovaSeq 6000 with the S4 reagent kit. Comparisons were made between methods (AMPure vs. unpurified, AMPure vs. MinElute, MinElute vs. unpurified) to assess the effects of purification method on downstream differential expression. Comparisons were also made within methods using the varying concentrations tested for unpurified samples and for MinElute purified samples to assess the effects of concentration on differential expression. Variations of the AMPure procedure were also compared to assess the effectiveness of the variations tested in comparison to the unmodified procedure. A subset of samples was selected for use with alignment and differential expression package comparison. Unpurified high concentration samples eluted in RNAse-free water were compared to unpurified high concentration samples eluted in BR5, a buffer from the PAXgene blood miRNA kit, with the expectation that there should be no or very few differentially expressed genes. Unpurified high concentration samples eluted in RNAse-free water were also compared to unpurified low concentration samples also eluted in RNAse-free water, with possibly a small number of differentially expressed genes anticipated. A third dataset of simulated RNA-seq data was created with a known rate of differential expression. These files were aligned using Bowtie2, HISAT2, kallisto, RSEM, Rsubread, Salmon, and STAR. Results were then analyzed for differential expression using ALDEx2, baySeq, DEGseq, DESeq2, edgeR, limma, NOISeq, PoissonSeq, and SAMseq. Differential expression results of all three comparisons were evaluated to determine which combinations provided the most reliable results for both real and simulated data.

  Study phs003001

• Next Generation Mendelian Genetics: Auriculocondylar syndrome (ACS)

  This project is part of an ongoing project to identify the molecular genetic basis of rare craniofacial disorders. This specific project involved the collection of DNA samples from four probands with severe manifestations of auriculocondylar syndrome and their parents. Detailed clinical phenotypic data is available on each proband. The sole purpose of this research is to identify the molecular cause(s) of auriculochondylar syndrome.

  Study phs000437

• Caregiving as a Natural Stressor in Studies of the Role of Genes That Affect Serotonin Function in Regulating Risk Factors for Coronary Heart Disease (CAREGIVER)

  The burden of caregiving for an ill relative has been shown to interact with existing comorbidities to increase risk of several health outcomes including metabolic syndrome and blood pressure reactivity. The CAREGIVER study was developed to compare cardiometabolic risk factors in caregivers and controls. These risk factors include physiologic measures, psychologic measures, neighborhood characteristics, and genetic and genomic factors. DNA and plasma were collected and used for examination of cardiometabolic and stress biomarkers, genotyping and methylation analysis.

  Study phs001747

• Development of targeted DNA sequencing panel for brain tumors

  A prompt and reliable molecular diagnosis for brain tumors has become crucial in precision medicine. While Comprehensive Genomic Profiling (CGP) has become feasible, there remains room for enhancement in brain tumor diagnosis due to the partial lack of essential genes and limitations in broad copy number analysis. In addition, the long turnaround time of commercially available CGPs poses an additional obstacle to the timely implementation of results in clinics. To address these challenges, we developed a CGP encompassing 113 genes, genome-wide copy number changes, and MGMT promoter methylation.

  Study EGAS50000000699