Search Results - EGA European Genome-Phenome Archive

WGS_of_healhy_mesothelial_cells_and_primary_mesothelima_cell_lines

Mesothelioma is a rare and aggressive cancer associated with previous exposure to asbestos. Currently there are no effective treatments for mesothelioma and majority of patients will die within a year after diagnosis. Although a large number of preclinical and clinical trials assessed the efficacy of various therapuetic modes, none of the tested molecules entered the clinic. Thus, to better understand what drives mesothelioma carcinogenesis and to identify novel targets for therapy, here we aim at performing WGS of heathy mesothelial cells and a panel of mesothelioma cells lines. Primary mesothelial cell lines were established in prof. Marciniak lab from human pleural specimens, while primary mesothelioma cell lines were obtained from MesobanK. Both models constitute low passage cell lines and therefore should closely represent genetics of the original tissue.

Study EGAS00001005559

A PROSTATE TUMORGRAFT PANEL TO ACCELERATE PRECISION MEDICINE

The management of advanced prostate cancer (PCa) has strongly evolved in the last decade with the introduction of the next generation of androgen receptor pathway inhibitors which have considerably improved patient outcomes. Most recently, the investigation of genomic landscape has provided targetable molecular alterations such as homologous gene DNA repair defects correlated with response to PARP inhibitors. Despite these significant advances, while localized PCa is generally associated with favorable outcome, metastatic PCa is currently considered incurable. For further investigations in precision treatment, the development of preclinical models representing the complex prostate tumor heterogeneity are mandatory. Accordingly, we aimed to establish a resource of patient-derived xenograft (PDX) models that exemplify each phase of this multistage disease for accurate and rapid evaluation of candidate therapies.

Study EGAS00001007033

NOTCH1 fusion genes in pediatric T-cell lymphoblastic lymphoma hallmark a common high-risk subgroup with blood TARC levels as possible biomarker

T-cell lymphoblastic lymphoma (T-LBL) is a common pediatric malignancy accounting for approximately 20% of the non-Hodgkin lymphomas during childhood. Survival rates of T-LBL are ~80%, but outcome after relapse is dismal, with salvage rates reaching only ~15. Considering the extremely poor prognosis after relapse and absence of clinically relevant high-risk genetics, there is an urgent need for the identification of molecular risk factors and new prognostic biomarkers in T-LBL, as well as identification of new therapeutic strategies. In this study we present a novel entity of high-risk pediatric T-LBL patients characterized by previously unknown NOTCH1 gene fusions and highly elevated blood TARC levels

Study EGAS00001007703

Multi-region sequencing of RCC with VTT and metastasis using WES and RNAseq

This dataset contains multi-region sequencing of 16 RCC patients with venous tumor thrombus (VTT), 11 of which were either metastatic on diagnosis or recurred with metastasis. Whole exome sequencing is available for 94 samples across all 16 patients, including 1 matched normal sample per patient, 2-3 primary tumor samples per patient, 1-2 VTT samples per patient, and 0-3 metastasis samples per patient (metastatic lesions were only sampled for 8 of the 11 metastatic patients). RNAseq, generated by exome capture, is available for 67 samples across 12 patients, including 0-1 matched normal samples per patient, 3 primary tumor samples per patient, 0-1 VTT samples per patient, and 0-3 metastasis samples per patient (RNAseq was only available for 4 of the 8 patients from whom metastatic lesions were sampled).

Dataset EGAD00001008441

May 2021 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.

May 2021 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 EGAD00001008100

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Multimodal Developmental Neurogenetics of Females

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 phs002043

Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Genomics of Autism Spectrum Disorder (GASD)

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 phs002509

Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Simons Searchlight

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 phs002512

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Autism Center of Excellence (ACE II)

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 phs002042

Genome Wide Association for Asthma and Lung Function

The SNP Typing for Association with Multiple Phenotypes from Existing Epidemiologic (STAMPEED) asthma project includes subjects with asthma and controls from the Chicago Asthma Genetics Study (CAG), NHLBI multicenter Severe Asthma Research Program (SARP) and NHLBI Collaborative Studies on the Genetics of Asthma CSGA (Wake Forest). All studies included European American and African American children and adults with asthma ranging from mild to severe and adult controls. CAG participants were collected at the University of Chicago. SARP participants were recruited at the NHLBI SARP sites with an emphasis on recruiting severe asthmatics (Moore et al, Am J Respir Crit Care Med, 2010, PMID: 19892860). CSGA cases and controls collected by the Wake Forest investigators were also included. Asthma status was based on both a physician's diagnosis and either bronchodilator reversibility or hyper-responsiveness to methacholine as well as less than 5 pack years of smoking. Genotyping was performed on the Illumina 1Mv1 platform, with individual genotypes called using clustering algorithms as implemented in the BeadStudio software by Illumina. The total number of markers following standard QC was 1,025,129. Imputation was performed using the HapMap phase 2, release 21 SNPs using MACH with the phased HapMap CEU and YRI haplotypes as a reference. Case/control association tests for asthma status were performed using logistic regression in R (http://CRAN.R-project.org/) on genotype dosages, and adjusting for the first principal component from EIGENSTRAT.

Study phs000355

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Study of Autism Genetics Exploration (SAGE)

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 phs001740

Center for Common Disease Genomics (CCDG)-Neuropsychiatric: A Study of the Genetic Causes of Complex Pediatric Disorders (CAG)

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 phs002004

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Autism Genetic Resource Exchange

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 phs001766

Center for Common Disease Genomics (CCDG) Neuropsychiatric: The Autism Simplex Collection (TASC)

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 phs001741

Center for Sub-Cellular Genomics

A cell is a highly complex system with distributed molecular physiologies in structured sub-cellular compartments whose interplay with the nuclear genome determine the functional characteristics of the cell. A classic example of distributed genomic processes is found in neurons. Learning and memory require modulation of individual synapses through RNA localization, localized translation, and localized metabolites, such as those from dendritic mitochondria. Dendrites of neurons integrate distributed synaptic signals into both electrical and nuclear transcriptional response. Dysfunction of these distributed genomic functions in neurons can result in a broad spectrum of neuropsychiatric diseases such as bipolar and depressive disorders, autism, among others. The Center for Sub-Cellular Genomics' (CSG) mission is to develop new technologies to enable the dissection of complex genomic interactions within a single cell. New technologies include methods to target DNA and RNA sampling at sub-cellular resolution in live cells; high-throughput isolation and microfluidics chemistry for sub-cellular fractions; sub-cellular resolution mass-spectrometry; and computational tools for analysis of sub-cellular genomics data. The new technologies developed by CSG will enable the broader genomics community to associate sub-cellular processes to cell function and dysfunction. These technologies will be utilized in the center to generate a comprehensive atlas of genomic signatures of sub-cellular compartments in the mammalian neuron system. The technologies and neuron-focused data obtained here will be relevant to neurodegenerative and neuropsychiatric diseases including schizophrenia, depression, autism spectrum disorder, traumatic brain injury, and Alzheimer's.

Study phs002120

Data access agreement for ATRT

Dac EGAC00001000306

Data Access Commitee for Schulte-Schrepping et al., 2020: Severe COVID-19 is marked by a dysregulated myeloid cell compartment

Dac EGAC00001001684

EGAD00010000498

Affymetrix SNP6.0 genotype data for prostate cancer patients

Dataset EGAD00010000498

EGAD00010000536

21 unlinked autosomal microsatellite loci for 30 Central Asian populations

Dataset EGAD00010000536

Variant_files_100_ID_trios

High Quality Variant Call files, generated by bioscope, converted to vcf format. Complete dataset for all 300 samples.

Dataset EGAD00001000277

Whole Exome Sequencing for Verhaak-GBM

Dataset EGAD00001001111

DATA FILES FOR BALL-PAX5-WES

Dataset EGAD00001001056

Whole Exome Data for Verhaak-GBM

Dataset EGAD00001001112

Whole Exome sequencing for Verhaak-GBM

Dataset EGAD00001001113

lnFXI_metaanalysis_summarydata

Summary data from Meta-analysis of Genome-Wide-Association Studies for plasma levels of Coagulation Factor XI (FXI)

Dataset EGAD00010001141

SAFIR02_Agilent

Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_agilent)

Dataset EGAD00010002243

AS_genotyping

AS genotyping data for lead SNPs using Illuminia Global Array V2.0

Dataset EGAD00010002476

DAC for the study molecular biomarkers associated with the diagnosis and severity of genetic and diseases from PAIDI-BIO354 GENYO-UGR)

Dac EGAC00001003090

WES for cell lines UWB1.289 and COV362

exon 11 mutated UWB1.289 and COV362 cell lines

Dataset EGAD50000000189

DAC for BCP-LBL Kiel

Whole exome sequencing and RNA sequencing of B-Cell Precursor Lymphoblastic Lymphoma tissue biopsies.

Dac EGAC50000000181

DAC for study involving the spatial transcriptomics analysis of HPV-dependent and HPV-independent vulval squamous cell carcinoma at Imperial College London.

Dac EGAC00001003515

Structural and Non-Coding Variants Increase the Diagnostic Yield of Clinical Whole Genome Sequencing for Rare Diseases

Study EGAS00001007575

Human embryo ATAC+RNA single cell sequencing samples DAC (Linnarsson)

DAC for human embryo ATAC+RNA single cell sequencing samples

Dac EGAC50000000657

Linnarsson lab general data access committe

Committee that handles the majority of policies for the Linnarsson Lab at Karolinska Institutet

Dac EGAC50000000835

DAC for datasets from study 'Single-nucleus multi-omic sequencing of the human motor cortex in ALS/ALS-FTD'

Dac EGAC50000000856

Aggregated count table

RNA-seq count matrix for 296 bulk pre-treatment tumors from IMblaze370

Dataset EGAD00001008552

Complete Genomics dataset for study EGAS00001002275.

TBD

Dataset EGAD00001003187

FGFP_16S

Firs 1106 16S rDNA data for the Flemish Gut Flora Project

Dataset EGAD00001001936

ICGC_Pedbrain_WGBS_Pilocytic_Astrocytoma

18 WGBS lanes for 9 samples of pilocytic astrocytoma.

Dataset EGAD00001005504

A Multiethnic Genome-wide Scan of Prostate Cancer

Multiple GWA studies of prostate cancer conducted in European White populations are ongoing. These studies will continue to have a dramatic impact on our understanding of the contribution of common genetic variation on inter-individual susceptibility to this common cancer. Important questions that will remain unanswered, however, are whether all common risk alleles for prostate cancer will be revealed in studies limited to populations of European ancestry. A comprehensive examination of common genetic variation in men of Japanese, Latino, and African ancestry will be required to understand population differences in disease risk and to reveal the full spectrum of causal alleles that exist in these populations. Further, genetic and environmental diversity is likely to contribute to ethnic heterogeneity of genetic effects. Elucidating gene x gene and gene x environment interactions is also likely to provide knowledge that may be critical for understanding the contribution of genetic susceptibility to racial/ethnic disparities in prostate cancer incidence and for translating the findings from GWA studies into interventions. In this study we plan to undertake a genome-wide association study (GWAS) of prostate cancer in the Multiethnic Cohort (MEC) Study. We propose the following hypotheses: (a) that inherited DNA variation influences risk of prostate cancer; (b) that many of the causal alleles will be outside known "candidate genes" requiring an agnostic, comprehensive search; and (c) that performing this search in a multi-ethnic cohort is more powerful than a study limited to a single population to reveal the full range of causal alleles relevant to the U.S. population. The version 1 release of this dataset will include genotype data for the Japanese and Latino populations in the study. The version 2 release will include data for the African ancestry population along with the Japanese and Latino subjects. The version 3 release will include fully-cleaned genotype data for all three populations. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to prostate cancer through large-scale genome-wide association studies of a well-characterized multi-ethnic cohort. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center and at the University of Southern California. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington. As an add-on to this GWAS we performed a targeted re-sequencing of all known prostate cancer risk loci in the samples from the MEC. Sequencing was performed in Dr. Reich's lab at Harvard Medical School.

Study phs000306

National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III)

The National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III) is a nationally representative cross-sectional survey of the U.S. general population, which was sponsored by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and conducted in 2012-2013. The NESARC-III's target population was the U.S. noninstitutionalized civilian population, 18 years and older, including residents of selected group quarters (e.g., group homes, workers' dormitories). Multistage probability sampling was used to randomly select respondents. Primary sampling units (PSUs) were individual counties or groups of contiguous counties, secondary sampling units (SSU) comprised groups of Census-defined blocks, and tertiary sampling units were households within SSUs. Finally, eligible adults within sampled households were randomly selected. Hispanics, Blacks, and Asians were oversampled and resulted in a total of 36,309 respondents. All respondents provided informed consent for survey participation. Data were adjusted for oversampling and screener - and person-level nonresponse, then weighted through post-stratification to represent the US civilian population based on the 2012 American Community Survey. These weighting adjustments were found to compensate adequately for nonresponse. Interviewer field methods involved initial structured home study, in-person training, ongoing supervision, and random respondent callbacks to verify data. The NESARC-III collected information on alcohol and drug consumption, alcohol use disorder, other substance use disorders (e.g., nicotine, cannabis and opioid), and associated physical and psychiatric adverse consequences. In addition to a full array of sociodemographic characteristics such as race/ethnicity, gender, age, risk and environmental factors including adverse childhood experiences (e.g., sexual, physical abuse and neglect) and family history for alcohol, drug use disorders and other psychiatric disorders (e.g., mood, anxiety, personality disorders and PTSD) were included (phenotypic variables=4,320). As part of the NESARC-III, 22,848 informative samples were genotyped on Affymetrix Axiom Exome Array consisting of 319,283 SNPs and 103,404 custom-selected SNPs Array (refer to the SNP annotation file). The latter array was selected based on the addiction associated genes, the results of 5 GWAS of alcohol and other psychiatric disorders, and animal models with addiction phenotypes. After filtering out poor quality SNPs using the standard Affymetrix pipeline there are 295,218 SNPs in the NESARC-III genetic data. The 22,848 subjects in this study were all deeply and consistently phenotyped via structured diagnostic interview. Controls group can be selected for specific disorders from a pool of all samples. Here are numbers of cases for major DSM-5 mental disorders in NESARC-III genetic data: Alcohol use disorder (7,075); Nicotine use disorder (6,641); Drug use disorder (2,570); Major depressive disorder (5,214); Persistent depression(1,429); Bipolar I (543); Anxiety disorders (4,226); PTSD (1,674); Personality disorders (4,014); Eating Disorders (457).

Study phs001590

Heart Failure Network Aldosterone Targeted Neurohormonal Combined with Natriuresis Therapy - (HFN ATHENA-BioLINCC)

ObjectiveTo assess whether high-dose spironolactone treatment for patients with acute heart failure lowers natriuretic peptide levels and improves outcomes better than usual care.BackgroundAcute heart failure (AHF) accounts for more than a million hospitalizations in the United States annually. The role of low-dose mineralocorticoid receptors antagonists (MRAs) therapy as a neurohormonal antagonist is well established for the treatment of chronic heart failure and reduced ejection fraction. However, the role of high-dose MRA therapy in AHF remained uncertain. A previous clinical trial suggested that the benefits of high-dose MRA therapy in AHF included lower natriuretic peptide levels, less congestion, better renal function, and less need for an intravenous diuretic. The use of intravenous loop diuretics can intensify secondary hyperaldosteronism among AHF patients, and hyperaldosteronism directly contributes to diuretic resistance in AHF. Elevated aldosterone levels in AHF are associated with an increased risk of cardiovascular mortality and HF readmission. Hospitalizations for heart failure are associated with increased risk of mortality and/or readmission.The HFN-ATHENA trial was conducted to determine if mineralocorticoid receptor antagonists administered at high doses relieved congestion, decreased diuretic resistance, and mitigated the effects of adverse neurohormonal activation in AHF.SubjectsThe ATHENA trial enrolled 360 participants. Of these, 178 participants were randomized to usual care treatment (placebo or low-dose spironolactone) and 182 participants were randomized to high-dose spironolactone.DesignThe study intervention was initiated within 24 hours of patients receiving the first dose of intravenous diuretics. Participants not taking spironolactone at enrollment were randomized to 100 mg spironolactone or a placebo. Participants taking low-dose spironolactone before their hospital admission were randomized to 100 mg or 25 mg per day in the usual care treatment arm. Prescription of all other medications, including diuretics, was left at the discretion of the treating physician. The study drug was discontinued after 96 hours and further MRA use was left to the treating physician's discretion. The primary end point was the proportional change in the log NT-proBNP levels from randomization to 96 hours (or at the hospital discharge if the discharge occurred earlier than 96 hours). Secondary endpoints included: (1) a clinical congestion score; (2) dyspnea relief; (3) daily cumulative net urine output for up to 96 hours; (4) net weight change from baseline to 96 hours or discharge (whichever came first); (5) furosemide equivalents of the loop diuretic dosage at discharge; and (6) the development of in-hospital worsening HF, with signs and symptoms requiring additional therapy.ConclusionsThere was no significant difference in the primary or secondary endpoints between the high-dose treatment arm and the usual care treatment arm.

Study phs003506

Multi-Modal Single-Cell, Spatial, and Genomic Analyses of Human Non-Small Cell Lung Cancer Brain Metastases

We performed single nuclei RNA-sequencing (snRNA-seq) with matched T cell receptor sequencing (TCR-seq), and pool matched low pass whole genome sequencing (WGS) of 12 treatment-naive non-small cell lung cancer (NSCLC) primary tumors (PTs) and 31 treatment-naive NSCLC brain metastases (BMs). In total, we recovered 277,206 cell transcriptomes in 43 samples. Single-nuclei suspension from frozen NSCLC metastases were generated using methods published in Slyper et al. (Nature Medicine, 2020, PMID:32405060) with modifications. The tissue was first cut in 20 µm sections using a cryostat and stored on dry ice until the next step. Then the tissue was put on wet ice and washed once with 5 ml PBS to remove OCT. After this step nuclei were extracted by vigorous pipetting in salt-tris buffer with Tween-20 (TST) followed by a high-volume wash in salt-tris buffer (ST). Nuclei were counted and 10,000-14,000 and were loaded using a Chromium controller (10X genomics) and Chromium Single Cell 5' Reagents (V1.1 and V2). Complementary DNA libraries were generated according to manufacturer's instructions, with the modification of one additional cycle of amplification. Matched single nuclei T cell receptor (snTCR) sequencing libraries were prepared from amplified cDNA libraries using either Chromium Single Cell V(D)J Enrichment Kit for human T cells Reagent Kit, v1.1, or single cell human TCR amplification kit. Final snTCR sequencing libraries were prepared using Single Index Kit T Set A for V1.1 libraries or Library construction kit and Dual Index Kit TT set A for V2 libraries. Sequencing libraries were quantified using Tapestation D5000 reagents and a 2200 TapeStation and pooled for sequencing. Pool matched low pass whole-genome sequencing (lp-WGS) was performed in addition to snRNA-seq to improve the identification of the malignant and non-malignant cell compartments. Nuclei from snRNA-seq sample preparations were collected by centrifugation (500g, 5 min), snap frozen after removing excess ST buffer, and stored at -200C until further processing. If insufficient nuclei (0C for 9 minutes. Adapters were not diluted, and the optional PCR (5 cycles) and cleanup were performed. After library cleanup with AMPure beads (Beckman Coulter, Brea, CA), libraries were quantified with Tapestation D5000 HS tapes (Agilent) and stored at -200C until sequencing.Using multiplexed immunofluorescence in an independent cohort of treatment-naïve pairs of primary tumors and brain metastases from the same patients with NSCLC, we validated genomic and tumor-microenvironmental findings and identified a cancer cell population characterized by neural features that strongly enriched in brain metastases. This comprehensive analysis provides insights into human NSCLC brain metastasis biology and serves as an important resource for additional discovery.

Study phs003865

Ludwig Center for Cancer Genetics and Therapeutics at Johns Hopkins

Dac EGAC00001000507

Data access committee for study - The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program "CASCADE".

Dac EGAC00001000574

Data Access Commitee for Dietrich and Wendisch et al., SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis (Submitted)

Dac EGAC00001001884

Data Access Commitee for Dietrich and Wendisch et al., SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis (Submitted)

Dac EGAC00001002335

EXOME_ARRAY_ANALYSIS

EXOME ARRAY ANALYSIS OF ADVERSE REACTIONS TO FLUOROPYRIMIDINE-BASED THERAPY FOR GASTROINTESTINAL CANCER

Dataset EGAD00010001499

DNA methylation for EGAS00001003603

Genome-wide DNA methylation profiling of Waldenstrom's macroglobulinemia (WM) patient samples

Dataset EGAD00010001861

NativeAmericans_InstitutoNacionaldeSalud_hg38_autosomic_3group

Genome-wide data for 130 Native American individuals from Peru

Dataset EGAD00010001992

NativeAmericans_InstitutoNacionaldeSalud_hg37_autosomic_1group

Genome-wide data for 71 Native American individuals from Peru

Dataset EGAD00010001991

NativeAmericans_InstitutoNacionaldeSalud_hg38_autosomic_2group

Genome-wide data for 59 Native American individuals from Peru

Dataset EGAD00010001990

BRACOVID_genotype

Cohort: Raw genotype files for BRACOVID cohort. Genotype Chip: Axiom_PMRA.r3 array genomic build: b37

Dataset EGAD00010002172

Genotype_HSM1_HSM2

Genotypes for 2 human skeletal muscle samples

Dataset EGAD00010002248

OICR-DAC, Ontario Institute for Cancer Research

Dac EGAC00001000591

OICR-DAC, Ontario Institute for Cancer Research

Dac EGAC00001000710

CCA NanoString data (60CCA)

Raw .RCC files for NanoString. nCounter PanCancer IO 360 Panel was used

Dataset EGAD00010002612

Sample Sheet

Sample sheet for aligning samples with patients.

Dataset EGAD50000000484

Lifelines NEXT HMO Data

The dataset contains HMO measurements for 1542 samples from Lifelines NEXT cohort

Dataset EGAD50000000531

Genome-wide array data from Eivissa and Menorca

DAC for the Genome-wide array data from 22 Eivissan and 20 Menorcan individuals.

Dac EGAC50000000297

Metadata associated with sequencing

Associated metadata for sequencing data.

Dataset EGAD50000000528

Analysis of circulating miRNAs for the identification of new prognostic and predictive markers in gastro-entero-pancreatic neuroendocrine tumour (GEP-NET)

Study EGAS00001007227

DAC anti-MPO BCR sequences

DAC for the requests of access to data of anti-MPO BCR sequences in the EGA repository,

Dac EGAC50000000446

NGS WGS Data - Unic TDP

WGS data from the Unicorn-PASS cohort for the Tandem Duplicator Phenotype paper

Dataset EGAD50000001567

UMCG Immunogenetics DAC

DAC for the data generated in the Immunogenetics group in the genetics department of the University Medical Center Groningen

Dac EGAC50000000785

Soegaard Laboratory Data Access Committee

Data Access Committee for data generated by the laboratory of Prof. O.S. Soegaard at Aarhus University Hospital.

Dac EGAC50000000888

Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

Dac EGAC50000000832

GATCI RNAseq fastqs

Raw RNA sequence data (fastq) for the GATCI project

Dataset EGAD00001005810

16S sequencing data for Butyricicoccus safety study

16S rRNA gene sequencing with Illumina MiSeq (V4 hypervariable region)

Dataset EGAD00001004406

BotSeq sequences1

This is the first dataset for the Botseq sequencing project

Dataset EGAD00001002263

Melanoma multi site metastases

These are caveman, pindel and sequenza calls for the metastatic melanoma exomes within this study.

Dataset EGAD00001005487

Genetic Predictors of Adverse Radiotherapy Effects (Gene-PARE)

The goal of this study was to identify SNPs and CNPs that are associated with development of normal tissue toxicities resulting from radiotherapy for prostate cancer. The study population includes approximately 1,400 men treated with brachytherapy, external beam radiation therapy, or a combination of the two treatments, and assessed for adverse effects at baseline and following radiotherapy. Three toxicity endpoints were investigated using a two-stage GWAS approach: urinary morbidity, rectal bleeding and erectile dysfunction. The study sample was split into a discovery set (N=367) and a replication set (N=417), and an additional 647 samples, which were not part of this original cohort, were also included as an independent replication set. The replication set was developed via collaboration developed under the framework of the Radiogenomics Consortium (RGC). The long-term goal of this project, and other radiogenomics projects lead by the RGC, is two-fold: 1) Develop an assay capable of predicting which cancer patients are most likely to develop radiation injuries resulting from treatment with a standard RT protocol, and 2) Obtain information to assist with the elucidation of the molecular pathways responsible for radiation-induced normal tissue toxicities. These studies focus on multiple cancer types including prostate, breast, lung, and head and neck cancers.

Study phs000772

Joslin Study on the Genetics of Type 2 Diabetes

Between 1993 and 2003, families were recruited in the Joslin Study on the Genetics of Type 2 Diabetes for the presence of an autosomal dominant mode of inheritance of diabetes. Recruiting and screening of families occurred through probands who were receiving medical care at the Joslin Clinic (Boston, MA). Screening of families included 1) a proband and at least one sibling with type 2 diabetes, 2) diabetes occurring in at least three generations, 3) diabetes inherited on one side of the prospective family. Probands had to have a diabetes diagnosis between the age range from 10 to 60 years. Demographic data, clinical data, and family history were collected from participating family members, along with blood and urine samples. This study includes genetic and phenotypic data from one family examined in Simeone, Wilkerson, et. al. (NPJ Genomic Medicine 2022, PMID: 35869090). Genotype data for 14 family members and whole genome sequencing data for 6 individuals were generated with the goal of identifying a potential genetic cause of disease in this family. To de-identify this family and protect confidentiality, information on sex in phenotype data and variants identified in X, Y, and MT chromosomes have been removed in compliance with IRB guidelines.

Study phs002959

Multicenter AIDS Cohort Study (MACS)

The Multicenter AIDS Cohort Study (MACS) - now part of the MACS-WIHS Combined Cohort Study (MWCCS) investigates the epidemiology of human immunodeficiency virus (HIV) infection among men who have sex with men. Over 7,000 participants volunteered for semiannual interview, physical examination, and laboratory testing across the 325 years of the study, in four metropolitan areas of Los Angeles, Chicago, Baltimore/Washington (DC) and Pittsburgh. The study aimed to identify risk factors for occurrence and clinical expression of the HIV infection, and to establish a repository of biologic specimens for future study. Study visits included detailed questions covering HIV-related symptoms and utilization of health services, demographic and psychosocial characteristics, a quality of life survey, a physical examination, a detailed form on medications used as prophylaxis and/or treatment, a neuropsychological screening and examination, blood samples to do measure hematologic variables including enumeration of T-cell subsets and HIV viral load and evaluate genetic risk factors via genome wide association studies using data generated using the Infinium Multi-Ethnic Global BeadChip genotyping array in all participants. Men who have sex with men, with and without HIV infection were enrolled in the MACS. MACS data continues to be available through the merged MWCCS cohort.

Study phs002226

CIP: Obesity-Diabetes Familial Risk, Viva La Familia Study

The VIVA LA FAMILIA Study was designed to identify genetic variants influencing childhood obesity and its comorbidities in the Hispanic population. Family recruitment and phenotyping were conducted in 2000-2005 in Houston, TX. All enrolled children (n=1030) and parents gave written informed consent or assent. The protocol was approved by the Institutional Review Boards for Human Subject Research for Baylor College of Medicine and Affiliated Hospitals and for Texas Biomedical Research Institute. The VIVA LA FAMILIA study design and methodology have been described in detail (Butte NF, 2006). Each family was ascertained on an obese proband, defined as a BMI > 95th percentile, between the ages 4-19 y. The cross-sectional, longitudinal study design consisted of baseline measurements, with a one-year. GWAS was performed using the Illumina HumanOmni1 v1.0 BeadChips on 815 children from 263 Hispanic families and HumanOmni 2.5-8v1 on an additional 43 children. Exome sequencing is being performed on 822 children using NimbleGen capture, followed by Illumina DNA sequencing. Butte NF, Cai G, Cole SA, Comuzzie AG. Viva la Familia Study: genetic and environmental contributions to childhood obesity and its comorbidities in Hispanic population. Am J Clin Nutr 2006;84(3):646-54. PMID: 16960181

Study phs000616

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

Genomic Studies of Gilles de la Tourette Syndrome

This study consists of three components. The first component includes genome-wide association study (GWAS) data on 695 TS cases and 198 ancestry matched controls from the first TS GWAS of 1285 TS cases and 4964 ancestry matched controls. The second component includes genome-wide association study (GWAS) data on 2106 TS cases from the second TS GWAS of 2716 TS cases and 3762 ancestry matched controls. The third component consists of 438 individuals representing 146 probands with DSM-IV-TR diagnosed Tourette Syndrome and their parents (146 complete parent-offspring trios). These individuals are part of the whole exome sequencing study, aiming to use whole exome sequencing of TS parent-offspring to identify de novo protein-truncating variants (PTVs) that are present in the child with TS but not in either parent. All subjects were collected by the Tourette Association of America International Consortium for Genetics (TAAICG) at seven sites in the United States and Canada. Both affected individuals and unaffected relatives were assessed for the presence of Tourette Syndrome and Chronic (Persistent) Tic Disorder (CTD) using a standardized, semi-structured interview, which has high clinical validity and reliability for the diagnoses of TS and CTD (TSAICG, Am J Hum Genet, 2007 (PMID: 17304708)); Darrow et al., Psychiatric Research, 2015 (PMID: 26054936)).

Study phs001380

NIDDK IBD Genetics Consortium Repository Immunochip

The Immunochip is a custom Illumina Infinium chip comprising 196,524 SNPs and small indels selected primarily based on GWAS analysis of 12 autoimmune and inflammatory diseases. The chip has two purposes: fine mapping of 289 established associations corresponding to 187 distinct loci, and deep replication of suggestive, but not yet proven, associations. Fine-mapping regions were defined as 0.2cM centered on GWAS hit SNPs, and all SNPs and short indels in these regions from the 1000 Genomes Project low coverage pilot CEU samples, as well as variants discovered in resequencing experiments conducted by groups collaborating in the chip design were selected for inclusion. Replication of autoimmune and inflammatory GWAS (including Crohn's disease and ulcerative colitis) contributed the bulk of the remaining SNP lists. Approximately 25,000 SNPs were included as replication of unrelated diseases as part of the WTCCC2 project, which serve as useful null SNPs for these analyses. In total, approximately 240,000 SNPs were selected for inclusion, with an assay design success rate of ~80%. Reprinted from Jostins et al. (2012), with permission from Springer Nature (see https://www.nature.com/reprints/permission-requests.html). Jostins, L., et al. (2012) Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature, 491, 119-24. PMID: 23128233.

Study phs001721

Germline hypomorphic CARD11 mutations in severe atopic disease

We described five patients from four unrelated families who had severe atopic dermatitis and susceptibility to mild skin viral infections. Some patients also exhibited other allergic symptoms such as asthma and food allergy. We performed targeted sequencing for affected patients A-I of family A and B-I of family B, whole exome sequencing for D-I, D-II.1 and healthy mother D-II.3 of family D, and whole genome sequencing for C-I and healthy mother C-II.2 of family C. We identified three different novel damaging missense mutations of CARD11 (GeneID:84433) in patients A-I (L194P), B-I (R975W), and C-I (E57D). In patients D-I and D-II.1, a dup183_196 (p.K196_V197insMKEERDSYNDELVK) mutation was found in the coil-coil domain of the protein. These mutations act as dominant negatives impeding the scaffolding function of the wild type protein, which leads to downstream NF-kB and mTORC1 signaling defects after TCR stimulation. Sanger sequencing later identified the corresponding CARD11 mutations in the affected family members (C-II.1, D-II.2) that are not included in the dbGaP submission. Hypomorphic CARD11 dominant negative mutants are novel causes of severe atopic disease.

Study phs001369

Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance through Serial Biopsies and Comprehensive Analytics

This dataset accompanies the manuscript "Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance Through Serial Biopsies and Comprehensive Analytics". In this study we discuss the clinical implications and consequences of molecular heterogeneity in a metastatic breast cancer patient identified through serial biopsies, multi-omic analysis, and longitudinal patient monitoring, performed through the precision oncology program, Serial Measurements of Molecular and Architectural Responses to Therapy (SMMART). This case study describes a metastatic breast cancer patient with a highly heterogenous tumor that began as ER positive/HER2 negative on diagnosis, then was found to be ER negative/HER2 positive in a metastatic liver lesion (Study biopsy #1), and finally triple negative (TNBC) in another metastatic liver biopsy (Study biopsy #2). Multi-omic assays included clinical genomic panel sequencing, clinical immunohistochemistry, a clinical protein profiling assay (Intracellular Signaling Protein Profiling), RNA sequencing, and RPPA. Here we provide the expression data from RNAseq and RPPA data on Study biopsy #2 for the patient discussed in this case report. Note: The first liver biopsy did not yield sufficient material for RNAseq or RPPA.Raw RNA FASTQ files from Study biopsy #2 of the liver Gene expression (RNAseq) files from Study biopsy #2Protein expression (RPPA) files (level 2, 3, 4) for Study biopsy #2

Study phs002321

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

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

Genomics and Epigenomics of the Elderly Response to Pneumococcal Vaccines

Pneumococcal Vaccine Study: This is a study designed to develop a detailed transcriptional and cellular profile of the immune response to pneumococcal vaccination with conjugated and non-conjugated polysaccharide vaccines in the senescent immune system of older adults. In this study, 39 healthy adults ages 60 and older that have never received pneumococcal vaccination, have been randomized to receive Prevnar 13 (Pfizer), a conjugated 13-valent vaccine or Pneumovax 23 (Merck), a non-conjugated 23-valent vaccine. Four (4) study visits occurred over 70 days at Day -7 (baseline), day 1, day 10 and day 60 (± 5d) post vaccination.Bulk RNA-sequencing data are available on the 4 time points for 31 of the participants and 1 replicate. ATAC-Doublet Detector Study: We generated single nucleus ATAC-seq (snATAC-seq) data from PBMCs of 2 baseline blood samples from the pneumococcal study. Generated data was then used to benchmark a novel computational method for detecting multiplets in snATAC-seq data, namely, AMULET (https://github.com/UcarLab/AMULET). Multiplets confound downstream analyses by introducing combined epigenomic profiles from 2 or more cells/nuclei. AMULET detects multiplets by using unique snATAC-seq data features that allow it to reliably use read counts to detect multiplets for their removal from data analyses.

Study phs002361

Germline Mutations and Developmental Mosaicism Underlying EGFR-Mutant Lung Cancer

We designed this study to examine the etiology of multiple lung tumors in EGFR-mutant non-small cell lung cancer patients who undergo surgical resection. Participants were 52-85 years old never or former smokers, who had at least 2 surgical lung tumor pathology specimens available in the Massachusetts General Hospital biobank, at least one of which had an EGFR mutation by routine clinical genotyping. 10 patients were selected, along with two patients from a family with an inherited EGFR-T790M mutation leading to multiple lung tumors. These patient tumor samples and matched normal lung samples were microdissected to collect DNA.In addition to obtaining clinical histories, we performed whole exome sequencing to evaluate the genetic profile of matched tumor and normal samples. The WES data are available on dbGaP. Our data showed increasing mutational burden and copy number alteration with increasing invasiveness, as compared to normal tissues, for the subset of samples that were assessed for tumor invasiveness. We also observed a range of numbers of shared mutations between tumors in a single patient, indicating different degrees of relatedness between lung tumors. We hope that this resource will help researchers understand non-small cell lung cancer presentations with multiple lung tumors. These data may aid in clinical decision making for such patients.

Study phs003379

Cardiovascular Health Study (CHS) - Imaging

The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of coronary heart disease (CHD) and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93. Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health. Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication, and mortality.

Study phs003639

NHLBI TOPMed - NHGRI CCDG: Atherosclerosis Risk in Communities (ARIC)

Participants from the Atherosclerosis Risk in Communities (ARIC) Study, a large population-based longitudinal cohort study, have been included in this Project and whole genome sequencing will be performed to contribute to analyses of early-onset atrial fibrillation and venous thromboembolism. Additional phenotype and genotype data are available for these individuals on dbGaP and can be accessed through the parent ARIC Cohort accession (phs000280). The National Heart, Lung and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program seeks to uncover factors that increase or decrease the risk of disease, identify subtypes of disease, and develop more targeted and personalized treatments. The Whole Genome Sequencing (WGS) Project is part of NHLBI's TOPMed program and serves as an initial step for the larger initiative.

Study phs001211

Melanoma Genome Sequencing Project

Melanoma is the most prevalent cause of skin cancer morbidity and mortality. In order to characterize the full range of somatic mutations that may drive the growth of melanoma, we are sequencing tumor and normal DNA from a set of roughly 150 melanomas. For the majority of samples (approximately 90% of the cases), mutations in protein coding genes will be assessed in the exonic DNA of tumor-normal pairs using hybrid capture and paired-end DNA sequencing. For a few of DNA samples (approximately 10% of the cases), the entire genomes will be analyzed to assess the possible contribution of complex structural rearrangements contributing to oncogenesis. The sequencing data are supplemented by copy number profiling on the same tumors using high-density SNP arrays. Integration of these approaches will enable the unbiased and comprehensive characterization of both known and novel recurrent DNA alterations that arise in melanoma.Versions 1-4 contain whole exome and bulk RNA sequencing data for patients with melanoma.Version 5 - We compared somatic genomic profiles from matched pre-treatment and post-resistance tumor biopsies in patients with metastatic melanoma who exhibited heterogeneous responses to immune checkpoint inhibitors (ICIs). This version includes whole exome sequencing (WES) data from 14 patients.

Study phs000452

3D tissue engineered human skeletal muscle modelling Facioscapulohumeral Muscular Dystrophy

acioscapulohumeral muscular dystrophy (FSHD) is caused by sporadic misexpression of the transcription factor double homeobox 4 (DUX4) in skeletal muscles. So far, monolayer cultures and animal models have been used to study the FSHD disease mechanism and for FSHD therapy development, but these models do not fully recapitulate the disease and there is a lack of knowledge on how DUX4 misexpression leads to skeletal muscle dysfunction. To overcome these barriers, we have developed a 3D tissue engineered skeletal muscle (3D-TESM) model by generating genetically matched myogenic progenitors (MPs) from human induced pluripotent stem cells of three mosaic FSHD patients. 3D-TESMs derived from genetically affected MPs recapitulate pathological features including DUX4 and DUX4 target gene expression, smaller myofiber diameters, and reduced absolute forces upon electrical stimulation. RNA sequencing data illustrates increased expression of DUX4 target genes in 3D-TESMs compared to 2D myotubes, and cellular differentiation was improved by 3D culture conditions. Treatment of 3D-TESMs with small molecules identified in drug development screens in 2D muscle culture showed no improvements in contractile force and sarcomere organization, highlighting the potential benefit of 3D-TESMs for preclinical drug potency screening by eliminating false-positive compounds for FSHD research and drug development.

Study EGAS50000000502

Use of new methodologies to achieve a thorough molecular characterization in pediatric acute leukemia

In childhood leukemia, a better genetic characterization is needed to define new clinic-biological entities, refine the risk-stratification of patients and help to reduce the toxicity by applying a risk-directed therapy. This project aims to obtain information that will allow us to personalize the management of pediatric patients with leukemia as much as possible, so that we can offer a complete diagnosis, a sensitive follow-up and a more targeted treatment to the real risk of each case. The use of massive genome analysis technologies such as transcriptome sequencing (RNA-Sequencing) will allow a comprehensive biological characterization of pediatric leukemia patients, especially those cases that we have not been able to characterize by conventional diagnostic techniques. We believe that the RNA-Seq technique will allow us to identify new biomarkers that will be useful for: 1) defining new biological entities with their own clinical behavior; 2) refining the stratification of patients into risk groups; 3) finding targets for a better follow-up of MRD and 4) identifying therapeutic targets for the application of targeted therapies to reduce toxicity. PI: Camós-Guijosa, Mireia; Vega-García, Nerea Funding: PI21/00213 Instituto de Salud Carlos III (ISCIII)

Study EGAS50000000701

National Cancer Institute (NCI) Early Onset Malignancies Initiative (EOMI): Molecular profiling of Breast, Colon, Kidney, Liver, Multiple Myeloma, and Prostate among Racially and Ethnically Diverse Populations

The Early Onset Malignancies Initiative (EOMI) is focused on collecting specimens from racially and ethnically diverse population groups with six different types of cancer (breast, prostate, colon, liver, kidney, and multiple myeloma). This initiative is a partnership between the Center for Research Strategy, the Center for Cancer Genomics and the Division of Cancer (DCP). DCP's NCI Community Oncology Research Program (NCORP) is a critical partner. The acquisition of the cancer and matching normal biospecimens in this initiative are from newly diagnosed early onset cancer patients who identify as Non-Hispanic Black, Hispanic, American Indian or Alaska Native, or Non-Hispanic White. The Minority/Underserved NCORPs sites will collect the samples for this project. By carrying out this initiative in the NCORP's national network of investigators, cancer care providers, and research institutions, the EOMI will harness the community-based partnerships to improve participation among these racial/ethnic groups. The NCORP investigators, as participants in NCI's clinical trials network, will annotate the biologic samples with clinical information that will enhance the ability to answer questions about molecular determinants of early disease, treatment response, and/or prognosis. The EOMI will be a step forward in addressing racial/ethnic disparities and in understanding cancer in underserved populations.

Study phs001952

Recurrent intra-tumour heterogeneity is a hallmark of metastatic prostate cancer

The evolution of cancers from low grade to metastatic disease is a major determinant of cancer mortality. Cancer evolution involves a complex interplay between cell intrinsic genetics and transcriptional alterations and the extrinsic microenvironment. To define the key mechanisms underpinning metastatic development, we focused on the most lethal form of prostate cancer, metastatic castration-resistant prostate cancer, and employed single-cell multi-omics and whole-genome sequencing to deeply profile 34 metastatic lesions from 9 patients obtained from rapid autopsy. We found that intra-tumour heterogeneity is an indicator of key evolutionary processes, characterised by recurrent tumour populations acting as critical functional components of the tumour ecosystem, irrespective of clonal and microenvironmental backgrounds. Unexpectedly, microenvironments across metastatic sites played a limited role while clonal evolution primarily promoted transcriptional noise. Intra-patient functional convergence of tumour ecosystems was observed across metastatic sites, pointing towards system-level selection pressures that drive the heterogeneity landscape of mCRPC. Our findings reveal functional evolutionary convergence of metastatic disease into units of intra-tumour heterogeneity identifying critical determinants of metastatic progression for therapeutic targeting. Note: matched WGS for some tumour single-cell experiments, as well as germline WGS for patients CA0027, CA0034, CA0035, CA0043, and CA0076, can be found in EGAS00001006598.

Study EGAS50000001312

Rapid detection of expanded short tandem repeats in personal genomics using hybrid sequencing.

Long expansions of short tandem repeats (STRs); i.e., DNA repeats of 2-6 nucleotides, are associated with some genetic diseases. Cost-efficient high throughput sequencing can quickly produce billions of short reads that would be useful for uncovering disease-associated STRs. However, enumerating STRs in short reads remains largely unexplored because of the difficulty in elucidating STRs much longer than 100 bp, the typical length of short reads. We propose ab initio procedures for sensing and locating long STRs promptly by utilizing the frequency distribution of all STRs and paired-end read information. We validated the reproducibility of this method using biological replicates and used it to locate an STR associated with a brain disease (SCA31). Subsequently, we sequenced this STR site in eleven SCA31 samples using SMRT? sequencing (Pacific Biosciences), determined 2.3-3.1 kb sequences at nucleotide resolution, and revealed that (TGGAA)- and (TAAAATAGAA)-repeat expansions determined the instability of the repeat expansions associated with SCA31. Our method could also identify common STRs, (AAAG)- and (AAAAG)-repeat expansions, which are remarkably expanded at four positions in an SCA31 sample. This is the first proposed method for rapidly finding disease-associated long STRs in personal genomes using hybrid sequencing of short and long reads.

Study JGAS000002

Genentech Colon Cancer Screen

Identifying and understanding changes in cancer genomes is essential for the development of targeted therapeutics. Here we analyse systematically more than 70 pairs of primary human colon tumours by applying next-generation sequencing to characterize their exomes, transcriptomes and copy-number alterations. We have identified 36,303 protein-altering somatic changes that include several new recurrent mutations in the Wnt pathway gene TCF7L2, chromatin-remodelling genes such as TET2 and TET3 and receptor tyrosine kinases including ERBB3. Our analysis for significantly mutated cancer genes identified 23 candidates, including the cell cycle checkpoint kinase ATM. Copy-number and RNA-seq data analysis identified amplifications and corresponding overexpression of IGF2 in a subset of colon tumours. Furthermore, using RNA-seq data we identified multiple fusion transcripts including recurrent gene fusions involving R-spondin family members RSPO2 and RSPO3 that together occur in 10% of colon tumours. The RSPO fusions were mutually exclusive with APC mutations, indicating that they probably have a role in the activation of Wnt signalling and tumorigenesis. Consistent with this we show that the RSPO fusion proteins were capable of potentiating Wnt signalling. The R-spondin gene fusions and several other gene mutations identified in this study provide new potential opportunities for therapeutic intervention in colon cancer.

Study EGAS00001000288

Single cell sequencing of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis

The quantity of tumor infiltrating lymphocytes (TILs) in breast cancer (BC) is a robust prognostic factor for improved patient survival particularly in triple negative and HER2-overexpressing BC subtypes. Whilst T cells are the predominant TIL population, the relationship between quantitative and qualitative differences in T cell subpopulations and patient prognosis remains unknown. We performed single-cell RNA sequencing (scRNA-seq) of 6311 T cells isolated from human BCs, and show for the first time that significant heterogeneity exists in the infiltrating T cell population. We demonstrated that high TIL BCs contained significant numbers of CD8+ T cells with features of tissue-resident memory T (TRM) cell differentiation and that these CD8+ TRM cells expressed high levels of immune checkpoint molecules and effector proteins. A CD8+ TRM gene signature developed from the scRNA-seq data was significantly associated with improved patient survival in early-stage triple negative breast cancer (TNBC) and provided better prognostication compared with CD8 expression alone. Our data suggests that CD8+ TRM contribute to BC immunosurveillance and are the key targets of modulation through immune checkpoint inhibition. Further understanding of the development, maintenance and regulation of TRM cells will be crucial for successful immunotherapeutic development in BC.

Study EGAS00001002845

Molecular characteristics in Burkitt lymphoma over age groups

Treatment optimization has improved the overall survival in Burkitt lymphoma (BL) patients but there are still relevant outcome differences between pediatric and adult patients. In both age groups survival remains poor for patients who suffer relapse. Therefore, new treatment approaches are warranted to improve survival. Thus, we conducted a comparative study in the largest pediatric cohort to date including 191 cases and 97 samples from adult patients and analyzed the mutational landscape. We detected overlapping molecular profiles but also significant differences in the mutational pattern. Samples from pediatric patients show a higher frequency of mutations in ID3, DDX3X and BAF-complex components ARID1A and SMARCA4, while YY1AP1 and BCL2 are more frequently mutated in cases from adult BL patients. Correlation of the mutational profile with clinical data was available for the pediatric cohort and identified TP53 mutations to be highly significantly associated with the incidence of relapse thus identifying the first molecular marker to be associated with the incidence of relapse in pediatric BL. As the hotspot analysis of TP53 mutations showed mostly gain of function mutations, it is tempting to speculate that drugs decreasing the amount of malignant TP53 or increase the abundance of wildtype TP53 could be a promising approach for future treatment regimens to further improve prognosis.

Study EGAS00001005270

Allele Balance Bias Identifies Systematic Genotyping Errors and False Disease Associations

In recent years, Next Generation Sequencing (NGS) has become a cornerstone of clinical genetics and diagnostics. Many clinical applications require high precision, especially if rare events such as somatic mutations in cancer or genetic variants causing rare diseases need to be identified. Although random sequencing errors can be modeled statistically and deep sequencing minimizes their impact, systematic errors remain a problem even at high depth of coverage. Understanding their source is crucial to increase precision of clinical NGS applications. In this work, we studied the relation between recurrent biases in allele balance (AB), systematic errors and false positive variant calls across a large cohort of human samples analyzed by whole exome sequencing (WES). We have modeled the allele balance distribution for biallelic genotypes in 987 WES samples in order to identify positions recurrently deviating significantly from the expectation, a phenomenon we termed allele balance bias (ABB). Furthermore, we have developed a genotype callability score based on ABB for all positions of the human exome, which detects false positive variant calls that passed state-of-the-art filters. Finally, we demonstrate the use of ABB for detection of false associations proposed by rare variant association studies (RVAS).

Study EGAS00001003027

Developmental_Dysplasia_of_the_Hip__DDH_

The National Joint Registry for England and Wales (NJR) has become established as one of the largest repositories of clinical information about patients undergoing hip and knee replacement. The primary aim of this proposal is to examine the feasibility of adding value to that clinical information by partnering it with a DNA dataset to allow its use to be extended to the study of the underlying pathogenesis of diseases of the hip and knee, and the complications of their treatment. We will do this 1) by establishing a mechanism for accessing and linking pseudo-anonymised demographic and phenotype data between the NJR database and the proposed DNA Biobank; 2) by validating the collection of postal DNA samples from consenting NJR patients; and 3) by genotyping genome-wide 900 patients with the condition developmental dysplasia of the hip (DDH) to find variants that play a role in this heritable condition. The successful demonstration that the NJR can be used to establish a DNA Biobank will provide a powerful platform to examine the genetic basis for a wide range of joint diseases, and the complications of their treatment. This proposal is to carry out the genotyping portion of this project on the current CoreExome array

Study EGAS00001000916

Comparison of structural variations from 10X Genomics linked-reads and conventional Illumina short-reads sequencing

Structural variations (SVs) are large genomic rearrangements that can drive many diseases. Conventional short-reads whole genome sequencing (cWGS) allows their identification with base-pair resolution, but suffers from high false discovery rate. cWGS taps in short-range information from short-reads while linked-reads sequencing (10XWGS) utilizes long-range information. 10XWGS allows linkage of short-reads originating from the same large DNA molecule with a unique barcode captured in a gel bead in emulsion. This mitigates alignment-based artefacts from cWGS especially in repetitive regions. However, the false discovery rate of this technology is unclear. In this study, we performed a comprehensive analysis of different type and size of SVs predicted from these two technologies. The SVs common between both technologies were found to be highly specific by PCR and Sanger sequencing while validation rate dropped for uncommon events. Further, we propose a novel enrichment approach for filtering out false positive calls from both the technologies independently. To this end, we trained a machine learning model for respective technologies and used it to characterise SVs from MCF7 cell line and a primary breast cancer tumor with high precision. This approach would be valuable in understanding true mechanisms driven by SVs in various diseases.

Study EGAS00001004093

Whole genome sequencing of tumour and normal paired samples of diffuse intrinsic pontine gliomas

Diffuse intrinsic pontine glioma (DIPG) have a universally dismal prognosis (median 9-12 months), with neither chemotherapeutic nor targeted agents showing any substantial survival benefit in clinical trials in children with these tumours. DIPG are highly infiltrative malignant glial neoplasms of the ventral pons, which due to their location within the brain, make them unsuitable for surgical resection and consequently have a universally dismal clinical outcome. Recent high-throughput sequencing approaches have revealed a striking prevalence of K27M mutations in the genes encoding the histone variants H3.3 (H3F3A) or H3.1 (HIST1H3B) in the childhood brain tumour DIPG. This K-to-M substitution confers a trans-dominant ablation of global H3K27 trimethylation, which likely profoundly alters gene expression through de-repression of polycomb repressive complex 2 (PRC2) target genes. Despite these advances in our understanding of the distinct biology of these tumours, approaches for specific novel therapeutic interventions are not clear, and little has been reported of the secondary mutations accompanying these changes. We carried out whole genome sequencing on a series of 20 tumour normal pairs of pre-treatment biopsy samples of DIPG, for which the patients underwent a safe stereotactic procedure, and whole exome sequencing on a further six tumour normal pairs obtained at autopsy.

Study EGAS00001000572

The evolutionary trajectory of a highly recurrent paediatric high grade neuroepithelial tumour with MN1:BEND2 fusion

Astroblastomas are rare brain tumours which predominate in children and young adults, and have a controversial claim as a distinct entity, with no established WHO grade. Reports suggest a better outcome than high grade gliomas, though they frequently recur. Recently, they have been described to overlap with a newly-discovered group of tumours described as ’high grade neuroepithelial tumour with MN1 alteration’ (CNS HGNET-MN1), defined by global methylation patterns and strongly associated with gene fusions targeting MN1. We have studied a unique case of astroblastoma arising in a 6 year old girl, with multiple recurrences over a period of 10 years, with the pathognomonic MN1:BEND2 fusion. Exome sequencing allowed for a phylogenetic reconstruction of tumour evolution, which when integrated with clinical, pathological and radiological data provide for a thorough understanding of disease progression, with initial treatment driving tumour dissemination along four distinct trajectories. Infiltration of distant sites was associated with a later genome doubling, whilst there was evidence of convergent evolution of different lesions acquiring distinct alterations targeting NF-κB. These data represent an usual opportunity to understand the evolutionary history of a highly recurrent childhood brain tumour, and provide novel therapeutic targets for astroblastoma / CNS HGNET-MN1.

Study EGAS00001002432

12255 results for "free coins ultimate team Visit Buyfc26coins.com for latest FC 26 coins news..G9vn"

in 40.86 milliseconds.

WGS_of_healhy_mesothelial_cells_and_primary_mesothelima_cell_lines

A PROSTATE TUMORGRAFT PANEL TO ACCELERATE PRECISION MEDICINE

NOTCH1 fusion genes in pediatric T-cell lymphoblastic lymphoma hallmark a common high-risk subgroup with blood TARC levels as possible biomarker

Multi-region sequencing of RCC with VTT and metastasis using WES and RNAseq

May 2021 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.

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Multimodal Developmental Neurogenetics of Females

Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Genomics of Autism Spectrum Disorder (GASD)

Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Simons Searchlight

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Autism Center of Excellence (ACE II)

Genome Wide Association for Asthma and Lung Function

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Study of Autism Genetics Exploration (SAGE)

Center for Common Disease Genomics (CCDG)-Neuropsychiatric: A Study of the Genetic Causes of Complex Pediatric Disorders (CAG)

Center for Common Disease Genomics (CCDG) Neuropsychiatric: Autism Genetic Resource Exchange

Center for Common Disease Genomics (CCDG) Neuropsychiatric: The Autism Simplex Collection (TASC)

Center for Sub-Cellular Genomics

Data access agreement for ATRT

Data Access Commitee for Schulte-Schrepping et al., 2020: Severe COVID-19 is marked by a dysregulated myeloid cell compartment

EGAD00010000498

EGAD00010000536

Variant_files_100_ID_trios

Whole Exome Sequencing for Verhaak-GBM

DATA FILES FOR BALL-PAX5-WES

Whole Exome Data for Verhaak-GBM

Whole Exome sequencing for Verhaak-GBM

lnFXI_metaanalysis_summarydata

SAFIR02_Agilent

AS_genotyping

DAC for the study molecular biomarkers associated with the diagnosis and severity of genetic and diseases from PAIDI-BIO354 GENYO-UGR)

WES for cell lines UWB1.289 and COV362

DAC for BCP-LBL Kiel

DAC for study involving the spatial transcriptomics analysis of HPV-dependent and HPV-independent vulval squamous cell carcinoma at Imperial College London.

Structural and Non-Coding Variants Increase the Diagnostic Yield of Clinical Whole Genome Sequencing for Rare Diseases

Human embryo ATAC+RNA single cell sequencing samples DAC (Linnarsson)

Linnarsson lab general data access committe

DAC for datasets from study 'Single-nucleus multi-omic sequencing of the human motor cortex in ALS/ALS-FTD'

Aggregated count table

Complete Genomics dataset for study EGAS00001002275.

FGFP_16S

ICGC_Pedbrain_WGBS_Pilocytic_Astrocytoma

A Multiethnic Genome-wide Scan of Prostate Cancer

National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III)

Heart Failure Network Aldosterone Targeted Neurohormonal Combined with Natriuresis Therapy - (HFN ATHENA-BioLINCC)

Multi-Modal Single-Cell, Spatial, and Genomic Analyses of Human Non-Small Cell Lung Cancer Brain Metastases

Ludwig Center for Cancer Genetics and Therapeutics at Johns Hopkins

Data access committee for study - The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program "CASCADE".

Data Access Commitee for Dietrich and Wendisch et al., SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis (Submitted)

Data Access Commitee for Dietrich and Wendisch et al., SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis (Submitted)

EXOME_ARRAY_ANALYSIS

DNA methylation for EGAS00001003603

NativeAmericans_InstitutoNacionaldeSalud_hg38_autosomic_3group

NativeAmericans_InstitutoNacionaldeSalud_hg37_autosomic_1group

NativeAmericans_InstitutoNacionaldeSalud_hg38_autosomic_2group

BRACOVID_genotype

Genotype_HSM1_HSM2

OICR-DAC, Ontario Institute for Cancer Research

OICR-DAC, Ontario Institute for Cancer Research

CCA NanoString data (60CCA)

Sample Sheet

Lifelines NEXT HMO Data

Genome-wide array data from Eivissa and Menorca

Metadata associated with sequencing

Analysis of circulating miRNAs for the identification of new prognostic and predictive markers in gastro-entero-pancreatic neuroendocrine tumour (GEP-NET)

DAC anti-MPO BCR sequences

NGS WGS Data - Unic TDP

UMCG Immunogenetics DAC

Soegaard Laboratory Data Access Committee

Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

GATCI RNAseq fastqs

16S sequencing data for Butyricicoccus safety study

BotSeq sequences1

Melanoma multi site metastases

Genetic Predictors of Adverse Radiotherapy Effects (Gene-PARE)

Joslin Study on the Genetics of Type 2 Diabetes

Multicenter AIDS Cohort Study (MACS)

CIP: Obesity-Diabetes Familial Risk, Viva La Familia Study

Transcriptomic Profiling of Oropharyngeal Squamous Cell Carcinoma

Genomic Studies of Gilles de la Tourette Syndrome

NIDDK IBD Genetics Consortium Repository Immunochip