13393 results for ""pdc"+"heritage+language"+census+study"

in 31.77 milliseconds.

• Reference epigenome CKD24_C_Podo_mRNA-Seq data generated from KEP study

  A CKD24_C_Podo_mRNA-Seq paired end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003482

• Reference epigenome CKD25_C_Podo_mRNA-Seq data generated from KEP study

  A CKD25_C_Podo_mRNA-Seq paired end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003483

• Reference epigenome OB57_D_PreA_mRNA-Seq data generated from KEP study

  A OB57_D_PreA_mRNA-Seq paired end data for Preadipocyte(fat)

  Dataset EGAD00001003487

• Reference epigenome OB56_N_PreA_smRNA-Seq data generated from KEP study

  A OB56_N_PreA_smRNA-Seq single end data for Preadipocytes(fat)

  Dataset EGAD00001003495

• Reference epigenome OB57_D_PreA_smRNA-Seq data generated from KEP study

  A OB57_D_PreA_smRNA-Seq single end data for Preadipocyte(fat)

  Dataset EGAD00001003496

• Reference epigenome CKD24_C_Podo_smRNA-Seq data generated from KEP study

  A CKD24_C_Podo_smRNA-Seq single end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003498

• Reference epigenome CKD25_C_Podo_smRNA-Seq data generated from KEP study

  A CKD25_C_Podo_smRNA-Seq single end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003499

• Reference epigenome IPS02_N_NPC_WGBS data generated from KEP study

  A IPS02_N_NPC_WGBS paired end data for Neural progenitor cells(Nestin)

  Dataset EGAD00001003474

• Reference epigenome IPS03_N_ENeuron_WGBS data generated from KEP study

  A IPS03_N_ENeuron_WGBS paired end data for Early neuron cells(Tuj1)

  Dataset EGAD00001003475

• SFHS pedigrees_X10

  Deep (>25x mean coverage) whole genome sequencing on 5-10 families drawn from the Scottish Family Health Study with four or more children.

  Dataset EGAD00001003211

• RNA sequencing data to study "A biobank of patient-derived pediatric braintumor models"

  RNA sequencing data for the PDOX model EPD-613FH

  Dataset EGAD00001003573

• STREP GENE Study Genome-wide Genotyping by Illumina Array

  Genotyping of 43 cases of invasive GAS infection by Illumina HumanCore-24 array and Illumina Global Screening Array.

  Dataset EGAD00001004558

• Multiple_myeloma_precursor_genomics

  Whole genome sequencing of up to 45 multiple myeloma precursor samples and matched normals pairs.

  Study EGAS00001006312

• Genomics of drug sensitivity in acute lymphoblastic leukemia

  Genomics of drug sensitivity in acute lymphoblastic leukemia

  Study EGAS00001006336

• OAC RNASeq

  Please see our related publication, 'Molecular profiling to predict immunochemotherapy outcomes in esophageal adenocarcinoma'

  Study EGAS00001006468

• Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Bolleboom-Gao peri-tumoral snRNA-seq glioblastoma dataset 2022/A

  Study EGAS00001006935

• SFHS pedigrees

  Deep (>25x mean coverage) whole genome sequencing on 5-10 families drawn from the Scottish Family Health Study with four or more children.

  Dataset EGAD00001001214

• RNAseq sample

  RNAseq sample used in study titled "Immune-awakening revealed by peripheral T cell dynamics after one cycle of immunotherapy".

  Dataset EGAD00001005747

• Reference epigenome Islet-derived-MSC01 WGBS data generated from KEP study

  Islet-derived-MSC01 WGBS paired end data

  Dataset EGAD00001007140

• Reference epigenome Islet-derived-MSC02 WGBS data generated from KEP study

  Islet-derived-MSC02 WGBS paired end data

  Dataset EGAD00001007141

• Reference epigenome Islet-derived-MSC03 WGBS data generated from KEP study

  Islet-derived-MSC03 WGBS paired end data

  Dataset EGAD00001007142

• Reference epigenome Islet-derived-MSC04 WGBS data generated from KEP study

  Islet-derived-MSC04 WGBS paired end data

  Dataset EGAD00001007143

• Reference epigenome Islet-derived-iPSC01 WGBS data generated from KEP study

  Islet-derived-iPSC01 WGBS paired end data

  Dataset EGAD00001007144

• Reference epigenome Islet-derived-iPSC02 WGBS data generated from KEP study

  Islet-derived-iPSC02 WGBS paired end data

  Dataset EGAD00001007145

• Reference epigenome Fat-adipocyte03 mRNA-Seq data generated from KEP study

  Fat-adipocyte03 mRNA-Seq paired end data

  Dataset EGAD00001007157

• Reference epigenome Fat-adipocyte04 mRNA-Seq data generated from KEP study

  Fat-adipocyte04 mRNA-Seq paired end data

  Dataset EGAD00001007158

• Reference epigenome Fat-adipocyte05 mRNA-Seq data generated from KEP study

  Fat-adipocyte05 mRNA-Seq paired end data

  Dataset EGAD00001007159

• Reference epigenome Pancreas-Islet06 mRNA-Seq data generated from KEP study

  Pancreas-Islet06 mRNA-Seq paired end data

  Dataset EGAD00001007166

• Reference epigenome Pancreas-Islet07 mRNA-Seq data generated from KEP study

  Pancreas-Islet07 mRNA-Seq paired end data

  Dataset EGAD00001007167

• Reference epigenome Pancreas-Islet08 mRNA-Seq data generated from KEP study

  Pancreas-Islet08 mRNA-Seq paired end data

  Dataset EGAD00001007168

• Reference epigenome SMC01 h3k4me3 ChIP-Seq data generated from KEP study

  SMC01 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007311

• Reference epigenome SMC05 h3k9me3 ChIP-Seq data generated from KEP study

  SMC05 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007336

• Reference epigenome ADMSC05 h3k27me3 ChIP-Seq data generated from KEP study

  ADMSC05 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007375

• PRDM13 exome sequencing set

  Exome sequencing study on 4 individuals from a pedigree with CHH and cerebellar hypoplasia.

  Dataset EGAD00001008420

• Reference epigenome Islet-derived_MSC06 mRNA-Seq data generated from KEP study

  Islet-derived_MSC06 mRNA-Seq paired end data

  Dataset EGAD00001007878

• Sanger sequencing of catalytic-domain encoding exons of tyrosine kinase genes from human endometrial tumor DNAs

  The purpose of the original study was to search for somatic mutations in the tyrosine kinome of serous and clear cell endometrial carcinomas (human). The study was conducted in two phases. Phase 1: A mutation discovery screen, in which ~577 exons encoding the catalytic domains of 86 tyrosine kinases were PCR-amplified and bidirectionally Sanger sequenced from 24 serous, 11 clear cell, and 5 mixed histology endometrial tumors. This was followed by alignment of sequence reads to the human reference sequence and subsequent nucleotide variant calling to identify potential somatic (tumor-specific) mutations. Potential somatic mutations were confirmed by re-amplification and sequencing of the relevant tumor DNA as well as matched non-tumor ("normal") DNA from the same case. Phase 2: A mutation prevalence screen, in which the non-catalytic regions two tyrosine kinase genes, TNK2 and DDR1, were PCR-amplified and sequenced from the 40 discovery screen tumors, and all coding exons of TNK2 and DDR1 were PCR-amplified and sequenced from another 10 clear cell, 21 serous, and 41 endometrioid endometrial tumors, in an effort to identify additional somatic mutations in each gene. Exons encoding the exonuclease domain of POLE were also sequenced to document somatic mutations.

  Study phs000841

• Predicting the Prevalence of Complex Genetic Diseases from Individual Genotype Profiles Using Capsule Networks

  Diseases with a complex genetic architecture, such as amyotrophic lateral sclerosis (ALS) as a most prominent example, are hard to disentangle. "Human mind-friendly" methods, such as linear approaches used in genome wide association studies (GWAS), remain blind to many genetic variants that matter. On the other hand, methods that are sufficiently sophisticated to entirely capture the characteristic interplay of genetic variants remain black boxes for the human mind. Here, we give this a decided, and as we argue, a very promising try. We present DiseaseCapsule, a capsule network-based approach that enables us to predict prevalence/occurrence of a genetically complex disease from individual genotype profiles. Importantly, capsule networks are considerably easier to decompose into their components than ordinary deep neural networks, which promotes the interpretability of their results. The data we used are from Project MinE, a large-scale study that aims to reveal the genetic and epigenetic mechanisms that underlie ALS in the framework of a globally concerted collaboration. Specifically, we used data from the Dutch cohort of the project, which contains 7213 healthy ('control') individuals and 3192 individuals affected with ALS. The cohort includes 5208 females and 5197 males. All participants of the study were genotyped using an Illumina 2.5M SNP array.

  Study phs003146

• Genetic Epidemiology of Lung Cancer Consortium GWAS of Familial Lung Cancer

  Familial lung cancer cases were collected by the Genetic Epidemiology of Lung Cancer Consortium (GELCC) recruitment sites: University of Cincinnati, Karmanos Cancer Institute at Wayne State University, Louisiana State University Health Sciences Center-New Orleans, Mayo Clinic, and Medical College of Ohio. Familial cases for this study came from three sources: 1) one case each from families (at least 3 affected lung cancer cases in the family) included in the linkage analysis; 2) one case from linkage-eligible families (at least 3 affected lung cancer cases in the family) but where there were insufficient biospecimens available to make them informative for linkage analysis; and 3) one case from families not eligible for the linkage study with a family history of at least one first or second degree relative affected with lung cancer. Unrelated controls were selected from 1) among the spouses of family members, thus matching on socio-economic status (SES) and ethnicity (typically) of the cases or 2) from case-control studies of lung cancer conducted in the same location in which the linkage families were collected and matched on age, sex, and race. All cases and controls self-reported as European American. Biospecimens used for normal DNA extraction included blood, saliva or mouthwash. Some samples underwent whole genome amplication.

  Study phs000629

• Genetic analysis of Hirschsprung disease

  Hirschsprung disease (HSCR) is a birth defect resulting from the absence of nerve (ganglion) cells in the gastrointestinal tract. Hirschsprung disease has a population incidence of 1/5,000 live births and most often occurs as an isolated condition. However, approximately 30% of HSCR cases are associated with other birth defects such as Down syndrome, deafness, hypopigmentation, and Congenital Central Hypoventilation syndrome (CCHS). Hirschsprung disease is a genetic condition with autosomal dominant, autosomal recessive, and multigenic patterns of inheritance described. The goal of the research study is to identify genes harboring causative HSCR mutations and to better understand the complex inheritance of HSCR in families using whole genome mapping and sequencing studies with functional follow-up of candidate genes and variants. We intend to ascertain the frequency with which mutations in any human gene lead to familial and isolated forms of HSCR. Clinical information is collected to allow investigation of possible genotype - phenotype correlations. The subject population consists of individuals diagnosed with HSCR and their unaffected relatives. Individuals/families are ascertained through support groups, web-based listings of research studies and genetic testing services, an educational study website, and referrals from genetic counselors and physicians. Blood, or tissue, samples are requested from affected individuals and their unaffected relatives.

  Study phs000497

• Mapping Systemic Lupus Erythematosus Heterogeneity at the Single Cell Level

  Patients with Systemic Lupus Erythematosus (SLE) display a complex blood transcriptome whose cellular origin is poorly resolved. Using single-cell RNA-seq, we profiled ~276,000 PBMCs from 33 children with SLE (cSLE) with different degrees of disease activity (DA) and 11 matched controls. Increased expression of Interferon-stimulated genes (ISGs) distinguished cSLE from healthy control cells. The high-ISG expression signature (ISGhi) derived from a small number of transcriptionally defined subpopulations within major cell types, including monocytes, CD4+ and CD8+ T cells, NK cells, cDCs, pDCs, B cells and especially plasma cells. Expansion of unique subpopulations enriched in ISGs and/or in monogenic Lupus-associated genes classified patients with the highest DA. Profiling of ~82,000 single PBMCs from adult SLE patients confirmed the expansion of similar subpopulations in patients with the highest DA. This study lays the groundwork for resolving the origin of the SLE transcriptional signatures and the disease heterogeneity towards precision medicine applications. Patient demographics, clinical and laboratory data and treatment are summarized and available. The genomic data for participant aHD2 will not be included in the dataset The study description is reprinted from Nehar-Belaid et. al. Nature Immunology, 2020, with permission from Nature Immunology Group

  Study phs002048

• Genome-Wide Analysis for Addiction Susceptibility Genes

  Genome wide analysis for addiction susceptibility genes is an affected sibling pair linkage study using subjects who were patients in methadone replacement treatment programs (MMTP). Such patients are highly addicted to opioids and usually to other addicting substances as well. For entry into the programs, patients had to be at least 18 years of age and had to satisfy DSM-IV criteria for opioid dependence. Despite their common substance use disorder diagnosis, patients enrolled in MMTPs generally have a heterogeneous mix of co-morbid psychiatric disorders including anti-social personality disorder, major depression and anxiety disorders, and often satisfy DSM-IV criteria of substance use disorders other than opioid dependence. Genetic analysis was carried out using genotyping data obtained from a 10K SNP array, and non-parametric linkage was assessed using MERLIN. This resulted in the identification of a linkage peak on 14q that overlapped the NRXN3 gene (neurexin 3), which was previously identified as a potential candidate gene for addiction, and subsequently identified as a target gene in other addiction studies and autism. In version 2 of this study, a text file containing 7704 SNPs with large allele frequency discrepancy as compared to 1000 Genomes is included. Users have the option to exlude these 7704 SNPs.

  Study phs001266

• Transcriptomic Profiling of Oropharyngeal Squamous Cell Carcinoma

  The study is a retrospective transcriptomic profiling of oropharyngeal squamous cell carcinoma. The pathologic database was queried for squamous cell carcinoma tumors originating from the anatomic oropharynx (tonsil or tongue base) with available samples from surgical archives. This retrospective RNA sequencing cohort included cases dating prior to the routine implementation of p16 immunohistochemistry (IHC) testing at our institution, therefore, p16 status was not required for inclusion in this study. Formalin-fixed paraffin-embedded (FFPE) tissue samples were sent to the UNC Lineberger Comprehensive Cancer Center (LCCC) Translational Genomics Lab (TGL) for RNA isolation using the Maxwell 16 MDx Instrument (Promega AS3000) and the Maxwell 16 LEV RNA FFPE Kit (Promega AS1260) following the manufacturer's protocol (Promega 9FB167). After a pathology review of a hematoxylin and eosin (H&E) stained slides to identify tumor area, RNA was extracted from unstained slides using macrodissection. Total RNA quality was measured using a NanoDrop spectrophotometer (Thermo Scientific ND-2000C) and a TapeStation 4200 (Agilent G2991AA). Total RNA concentration was quantified using a Qubit 3.0 fluorometer (Life Technologies Q33216). Libraries were prepared with Illumina TruSeq Stranded Total RNA with Ribo-Zero protocol. Libraries were sequenced on an Illumina HiSeq2500 sequencer. Paired end read data, with read lengths of 75 were collected.

  Study phs002935

• Gabriella Miller Kids First Pediatric Research Program for Infantile Hemangiomas Associated with Multi-Organ Structural Birth Defects

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Infantile hemangiomas are the most common benign vascular tumor in infants, affecting 4-5% of children. Thirty percent of segmental infantile hemangiomas on the face and scalp are associated with birth defects of multiple organs. This condition is known as PHACE, an acronym for posterior fossa brain malformations, segmental facial hemangiomas, arterial anomalies, cardiac defects, eye anomalies, and sternal clefting. Genomic analysis of PHACE will inform treatment and expand knowledge about the causes of birth defects affecting the brain, arteries, heart, eye, midline development and hearing. The knowledge gained in this study will be used to drive strategies for prevention and provide critical targets for treatments for a range of birth defects and infantile hemangiomas.

  Study phs001785

• A Large Data Resource of Genomic Copy Number Variation across Neurodevelopmental Disorders

  This study presents the first genome-wide copy number variation (CNV) analysis across autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), and obsessive-compulsive disorder (OCD). A total of 2,691 subjects diagnosed with a neurodevelopmental disorder (NDD), and a total of 1,769 unaffected family members from Ontario, Canada were assayed using the Affymetrix CytoScan HD array. We identified rare CNVs, (< 0.1% frequency in 10,851 population control samples), and found clinically relevant CNVs in 10.5% of total subjects. Among all NDD subjects, we identified 17 (0.63%) with aneuploidies and 115 (4.3%) with known genomic disorder variants. We searched further for genes impacted by different CNVs in multiple disorders. Examples of NDD-associated genes linked across more than one disorder (listed in order of occurrence) are NRXN1, SEH1L, LDLRAD4, GNAL, GNG13, MKRN1, DCTN2, KNDC1, PCMTD2, KIF5A, SYNM, and long non-coding RNAs: AK127244, NRON, and PTCHD1-AS. We demonstrated that identical CNVs or genes could potentially contribute to the etiology of multiple NDDs. The CNVs identified will serve as a useful resource for both research and diagnostic laboratories for prioritization of variants and clinical interpretations.CNV data from this study are available through dbVar at https://www.ncbi.nlm.nih.gov/dbvar/studies/nstd173/.

  Study phs001881

• Genomic Wide Scans for Female Osteoporosis Genes

  Osteoporosis is a condition of excessive skeletal fragility which results in high risk to low trauma fractures. It is the most prevalent metabolic bone disease and is a major public health problem which may result in devastating morbidity and mortality. The most powerful, measurable determinant of fracture risk is bone mineral density (BMD). More than 60% of BMD variation is attributable to genetic factors. There are gender differences in BMD that contribute to a substantially higher fracture risk among women than men. Genetic studies demonstrate that some osteoporosis risk genes/genomic regions are gender specific. However, specific such genes contributing to female BMD and to the sex differences of BMD are largely unknown. Recent rapid progresses in SNP genotyping technology, in our knowledge about human genome diversity and linkage disequilibrium (LD) patterns in the human genome as revealed have made it feasible and timely to pursue a powerful whole genome-wide association study (GWAS) to identify genes for BMD. The major goal of this project is to perform a powerful GWAS study in a large sample of US Caucasian subjects. Gender specific effects of the genetic variants will be examined. The significant genetic variants discovered will be used to design diagnostic DNA chips for prognosis for potential health problems of osteoporosis later in life.

  Study phs000390

• Profiling RNA Translation in Pediatric Medulloblastoma

  This study provides RNA-sequencing and ribosome profiling data for patient-derived cell lines and patient tissue samples for children with medulloblastoma. Ribosome profiling is a variant protocol of RNA-sequencing that directly sequences ribosome-bound RNA fragments only. Associated RNA-seq and Ribo-seq data obtained separately for some cancer cell lines can be found on the NCBI SRA as PRJNA957428. Samples were processed for poly-A mRNA sequencing using the Roche Kapa Kit. Ribosome profiling was performed as described in the manuscript referenced below (Hofman et al.) and based on the article by McGlincy et al., Methods (2017). Ribo-seq data were analyzed for sample quality using RiboseQC (Calviello, Nat Struct Mol Biol, 2020). These data were used to quantify P-sites of open reading frames. RNAseq and ribo-seq data were integrated and compared to determine translational efficiency values using TPM (Ribo-seq) over TPM (RNA-seq) as the metric. Ribo-seq data on 14 samples and RNAseq data on 21 samples derived from 16 fresh-frozen surgical samples for medulloblastoma and 5 autopsy samples are available through dbGaP. A second cohort of 4 medulloblastoma samples (RNAseq, Ribo-seq) related to this study can be found on the EGA at EGAS00001007426.

  Study phs003446

• Experimental and Clinical Studies of Presbycusis

  This study aimed to investigate genes and variants associated with adult-onset progressive hearing loss, a common and complex disease with a strong genetic component.Participants enrolled in an ongoing longitudinal study of age-related hearing loss at the Medical University of South Carolina (MUSC), dating from 1987. Pure tone thresholds at 0.25, 0.5, 1.0, 2.0, 3.0, 4.0, 6.0 and 8.0 kHz were obtained for each ear of each person, along with questionnaire responses concerning noise exposure history. Based on the audiometry, participants were classified into 5 groups as "Older-Normal", "Metabolic", "Sensory", "Unclassified" and "Unselected" by their hearing loss.Exome sequencing was carried out using the Agilent SureSelect X2 Target Enrichment System (version 5) and the Agilent SureSelect Human All Exon V5 kit, which included 5' and 3' UTRs. DNA was sheared using the Covaris S220 focused ultrasonicator. Libraries were sequenced on the Illumina HiSeq 2500. Variant loads per gene were calculated and compared between groups. Individual variants affecting hearing thresholds were also identified. Analyses were followed up in a second cohort. Several genes and variants were identified as novel candidates associated with both better and worse hearing. Data available through dbGaP include whole exome sequencing (WES) files and audiometric phenotyping.

  Study phs003327

• Genetic Predictors of Ibrutinib-Related Cardiovascular Side Effects in Patients with Chronic Lymphocytic Leukemia

  The goal of this study was to identify genetic polymorphisms associated with ibrutinib-related cardiovascular side effects (CVSEs). This is an observational non-interventional pharmacogenomic study of 50 patients with newly diagnosed or relapsed refractory chronic lymphocytic leukemia (NDCLL or RRCLL) receiving ibrutinib 420 mg for at least six months. The ibrutinib-related CVSEs included atrial fibrillation and hypertension, which occurred in 20% of patients. DNA obtained from buccal swabs was genotyped for 40 single nucleotide polymorphisms (SNPs) in GATA4, SGK1, KCNQ1, KCNA5, NPPA, and SCN5A using a customized next generation sequencing panel. It was found that GATA4 rs804280 AA (P =.043), KCNQ1 rs163182 GG (P =.036) and KCNQ1 rs2237895 AA (P =.023) were associated with the ibrutinib-related CVSEs. Patients with a high-risk score had at least two of the three significant risk genotypes identified in univariate analysis for GATA4 rs804280 A>C, KCNQ1 rs162182 G>C and KCNQ1 rs2237895 A>C, and patients with a low-risk score had either one or none of these genotypes. In multivariate analysis, 18 patients with at least two of the three high-risk genotypes had an 11.5-fold higher odds of CVSEs (P =.019; 1.79-119.73 at 95% CI).

  Study phs003370

• Gene Expression and Biomarker Utility in Post-Mortem Samples

  The FAA Functional Genomics Team examined the feasibility of analyzing gene expression profiles using post-mortem brain, lung, muscle, and blood samples collected from aviation accident fatalities, with the goal of validating post-mortem extracted RNA for use in RNA sequencing. We compared the RNA sequencing results obtained from THC-positive and THC-negative samples to determine whether RNA sequencing on samples collected from aviation accident fatalities was possible and if any differences in gene expression associated with THC consumption were detectable post-mortem. The study population included 57 males of indeterminant age who perished in general aviation accidents and for whom post-mortem toxicological testing identified delta-9-THC or its primary or secondary metabolites, as well as negative controls. We determined that RNA sequencing on post-mortem aviation accident fatality samples is possible, and further identified genes showing differential expression in lung and muscle between THC-positive and THC-negative samples. We conclude that post-mortem tissue samples collected from aviation accident fatalities are suitable for gene expression profiling, but caution researchers that such samples have low RNA integrity numbers and some degree of microbial contamination is both probable and to be expected. Raw sequencing files (.fastq) from this study are available in dbGaP.

  Study phs003546

• Molecular Characterization of Prostate Cancer Specimens by Bulk and Single Cell Analysis

  Version 1: We performed single-cell RNA-sequencing (scRNA-seq) of fresh biopsies from metastatic castration resistant prostate cancer. Additionally, where available, we performed matched bulk whole exome sequencing (WXS; tumor and normal paired) and whole transcriptome sequencing for the same individuals. We also performed bulk whole exome (WXS) and RNA-sequencing (RNA-Seq) from FFPE pre-treatment biopsies from patients with clinically localized high-risk prostate cancer.Version 2: We added data from a randomized phase 2 trial of radium-223 with or without pembrolizumab in patients with Metastatic Castration-Resistant Prostate Cancer (mCRPC) to bone. After enrollment, study participants underwent bone biopsy and were randomized 2:1 to receive radium-223 at 55 kBq/kg every 4 weeks + pembrolizumab at 200 mg every 3 weeks (Arm A, R223+P) or radium-223 at 55 kBq/kg every 4 weeks alone (Arm B, R223). Stratification factors were alkaline phosphatase ≥220 vs. Data generated includes bulk whole exome sequencing (WXS), ultra-low pass whole genome sequencing (WGS) at 0.1X coverage, and targeted-capture sequencing. The ultra-low pass sequencing was used as part of the selection criteria for the target capture sequencing. Note: Two subjects in this study are linked to phs001577 and phs000915 respectively.

  Study phs001988