B87252aa-b3c4-4aa7-8927-5e157590f12f - samples
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ABSTRACT:
PROVIDER: EGAD00001008771 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:DNA was isolated from whole red blood cells from various lines and crosses of broiler chickens. DNA was genotyped using Axiom genome-wide chicken array and cel files were analyzed using Axiom Analysis Suite Software (version 3.0.1) with Gallus gallus 5.0 using the software's Best Practices for agricultural animals. The results were exported (Genotyping_Data-3-21-2018.vcf) for all genotype calls and text file of all SNPs with >= 97% call rate rate was also produced for filtering the VCF file (ALL_SNPSs_with_Call_Rate_97_Plus_3-21-2018).
2019-05-25 | GSE131764 | GEO
Project description:File content a .vcf of 48 samples of Phaseolus lunatus
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Project description:Nucleotide-binding oligomerization domain 2 (Nod2) signaling is critical for human health.To figure out the clinical relevance of NOD2 ligands, the investigators plan to evaluate the change of NOD2 ligands in inflammatory bowel diseases (IBD), CRC, atherosclerotic cardiovascular disease (ACVD), and type 2 diabetes mellitus (DM2 ).
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Project description:To try to investigate the mechanism behind the adaptive phenotypes observed in a mice model model of HD crossed with mGluR5 knockout, we analyzed whether mutated huntingtin (Htt) expression in a mGluR5 null background could be altering the expression of genes that might be involved in the pattern of Htt aggregation and HD-related locomotor alterations. In this data set, we include analysis of gene expression in striatum of mice with four different genotypes: HdhQ20/Q20/mGluR5+/+; HdhQ20/Q20/mGluR5-/- ; HdhQ111/Q111/mGluR5+/+ ; HdhQ111/Q111/mGluR5-/-
2013-08-28 | GSE50379 | GEO
Project description:Our work illustrates how high-resolution molecular and spatial profiling of COVID-19 patient tissues collected during rapid autopsies can serve as a hypothesisgenerating tool to identify key mediators driving the pathophysiology of COVID-19 for diagnostic and therapeutic target testing. Here we employ bulk RNA sequencing to identify key regulators of COVID-19 and list specific mediators for further study as potential diagnostic and therapeutic targets. We use single-nuclei RNA sequencing to highlight the diversity and heterogeneity of coronavirus receptors within the brain, suggesting that it will be critical to expand the focus from ACE2 to include other receptors, such as BSG and ANPEP, and we perform digital spatial profiling of lung and lymph node tissue to compare two patients with different clinical courses and symptomatology.
2021-08-20 | GSE182298 | GEO
Project description:Our work illustrates how high-resolution molecular and spatial profiling of COVID-19 patient tissues collected during rapid autopsies can serve as a hypothesisgenerating tool to identify key mediators driving the pathophysiology of COVID-19 for diagnostic and therapeutic target testing. Here we employ bulk RNA sequencing to identify key regulators of COVID-19 and list specific mediators for further study as potential diagnostic and therapeutic targets. We use single-nuclei RNA sequencing to highlight the diversity and heterogeneity of coronavirus receptors within the brain, suggesting that it will be critical to expand the focus from ACE2 to include other receptors, such as BSG and ANPEP, and we perform digital spatial profiling of lung and lymph node tissue to compare two patients with different clinical courses and symptomatology.
2021-08-20 | GSE182297 | GEO
Project description:Our work illustrates how high-resolution molecular and spatial profiling of COVID-19 patient tissues collected during rapid autopsies can serve as a hypothesisgenerating tool to identify key mediators driving the pathophysiology of COVID-19 for diagnostic and therapeutic target testing. Here we employ bulk RNA sequencing to identify key regulators of COVID-19 and list specific mediators for further study as potential diagnostic and therapeutic targets. We use single-nuclei RNA sequencing to highlight the diversity and heterogeneity of coronavirus receptors within the brain, suggesting that it will be critical to expand the focus from ACE2 to include other receptors, such as BSG and ANPEP, and we perform digital spatial profiling of lung and lymph node tissue to compare two patients with different clinical courses and symptomatology.
2021-09-03 | GSE183356 | GEO
Project description:<p><b>LOCATION CHANGE FOR ALZHEIMER'S DISEASE SEQUENCING PROJECT (ADSP) DATA:</b> Please go to <a href="https://dss.niagads.org/" target="_blank">NIAGADS DSS</a> to apply for build 38 ADSP genetic and phenotypic data. See Background below for more details. For instructions on how to access the additional ADSP data that are shared through <a href="https://dss.niagads.org/" target="_blank">NIAGADS DSS</a>, visit the <a href="https://dss.niagads.org/documentation/" target="_blank">Application Instructions</a> page.</p> <p>Background: Additional sequencing data are continuously being generated by the ADSP. These data are mapped to the latest Genome Reference Consortium human genome build GRCh38 (hg38) and are being shared through the NIA Genetics of Alzheimer's Disease Data Storage Site (<a href="https://www.niagads.org/" target="_blank">NIAGADS</a>) Data Sharing Service (<a href="https://dss.niagads.org/" target="_blank">DSS</a>). As of May 1, 2020 there are 4,789 whole genomes and 19,922 whole exomes available to the research community. Later in 2020 there will be a total of ~17,000 whole genomes and 19,922 whole exomes available through NIAGADS DSS (<a href="https://dss.niagads.org/datasets/ng00067/" target="_blank">ng00067</a>). The total number of genomes from multi-ethnic cohorts is anticipated to exceed 50,000. Please see the <a href="https://www.niagads.org/adsp/content/study-design">ADSP Design</a> page for the complete study description.</p> <p>ADSP whole exome and whole genome sequence data that were shared through dbGaP were mapped to the GRCh37 (build 37). These data are from the Discovery Phase of the project (described below) and will continue to be available at this site.</p> <p><b>STUDY DESCRIPTION FOR dbGaP BUILD 37 ADSP DATA: </b>The overarching goals of the Alzheimer's Disease Sequencing Project (ADSP) are to: (1) identify new genomic variants contributing to increased risk of developing Alzheimer's Disease (AD), (2) identify new genomic variants contributing to protection against developing AD, and (3) provide insight as to why individuals with known risk factor variants escape from developing AD. These factors will be studied in multi-ethnic populations in order to identify new pathways for disease prevention. Such a study of human genomic variation and its relationship to health and disease requires examination of a large number of study participants and needs to capture information about common and rare variants (both single nucleotide and copy number) in well phenotyped individuals.</p> <p>Using existing samples from NIH funded and other studies, three NHGRI funded Large Scale Sequencing and Analysis Centers (LSAC) - Broad, Baylor, and Washington University - produced the DNA sequence data. Variant call data are being made available to the scientific community through NIH-approved data repositories. Statistical analysis of the sequence data is anticipated to identify new genetic risk and protective factors. The ADSP will conduct and facilitate analysis of sequence data to extend previous discoveries that may ultimately result in new directions for AD therapeutics. Analysis of ADSP data will be done in two phases.</p> <p>The Discovery Phase analysis (2014-2018) is funded under <a href="http://grants.nih.gov/grants/guide/pa-files/PAR-12-183.html">PAR-12-183</a>. The entire Discovery dataset contains whole-genome sequencing data on 584 subjects from 113 families, and pedigree data for > 4000 subjects; whole exome sequencing data on 5096 cases 4965 controls; and whole exome sequence data on an additional 853 (682 Cases [510 Non-Hispanic, 172 Hispanic]), and 171 Hispanic Control subjects from families that are multiply affected with AD.</p> <p>The Replication Phase (2016-2021) analysis will be funded under <a href="http://grants.nih.gov/grants/guide/rfa-files/RFA-AG-16-001.html">RFA-AG-16-001</a> and <a href="http://grants.nih.gov/grants/guide/rfa-files/RFA-AG-16-002.html">RFA-AG-16-002</a> and is expected to include a combination of genotyping and sequencing approaches on at least 30,000 subjects. Targeted sequencing will be done by the LSACs.</p> <p><b>GRCh37 Data Releases</b></p> <ul> <li>The <b>first</b> ADSP data release occurred on November 25, 2013. It included the whole-genome sequencing data in BAM file format on 410 individuals.</li> <li>The <b>second</b> ADSP data release occurred on March 31, 2014, and included the whole-genome sequencing data in BAM file format for an additional 168 individuals.</li> <li>The <b>third</b> ADSP data release occurred on November 03, 2014 and included whole-exome sequencing data in BAM file format for 10,939 individuals.</li> <li>The <b>fourth</b> ADSP data release occurred on February 13, 2015 and included revised ethnic data for subjects with whole-exome sequencing data.</li> <li>The <b>fifth</b> ADSP data release occurred on July 13, 2015 and included whole-genome genotypes and updated phenotypes as well as changes to pedigree structures and sample IDs.</li> <li>The <b>sixth</b> ADSP data release occurred on December 8, 2015, and included whole-exome genotypes and updated phenotypes as well as changes to subject IDs.</li> </ul> <p>This <b>seventh ADSP data release on April 12, 2016</b> includes: </p> <ul> <p>(1) WES and WGS SNV VCF files</p> <p>(2) WES and WGS Indel PLINK files</p> </ul> <p><b>ADSP Data Available through dbGaP:</b></p> <p> <table border="1"> <tr> <th></th> <th><b>ADSP - Whole Genome Sequencing</b></th> <th><b>ADSP - Whole Exome Sequencing</b></th> <th><b>Comments</b></th> </tr> <tr> <td>DNA-Seq (BAM)</td> <td>n=578</td> <td>n=10913</td> <td>Sequence data available (plus n=38 replications w/out genotype data)</td> </tr> <tr> <td>Concordant SNV Genotypes (PLINK format)</td> <td>N/A</td> <td>n=10913</td> <td>QC'ed genotypes that are concordant between the Atlas (Baylor's) and GATK (Broad's) calling pipelines (a subset of the consensus genotype set)</td> </tr> <tr> <td>Consensus Genotypes (PLINK and VCF format)</td> <td>n=578</td> <td>n=10913</td> <td>QC'ed genotypes that are concordant between Atlas and GATK pipelines as well as those that that were called uniquely by Atlas or GATK</td> </tr> <tr> <td>Concordant Indel Genotypes (PLINK format)</td> <td>n=578</td> <td>n=10913</td> <td>QC'ed genotypes that are concordant between the Atlas and GATK calling pipelines</td> </tr> <tr> <td>Phenotype Data</td> <td>n=4735</td> <td>n=10913</td> <td>Data of n=53 phenotype variables available (plus administrative data), including APOE genotype. WGS phenotypes include data of connecting family members.</td> </tr> </table> </p> <p>Please use the <a href="ftp://ftp.ncbi.nlm.nih.gov/dbgap/studies/phs000572/phs000572.v7.p4/">release notes</a> provided by dbGaP to obtain detailed information about study release updates. </p> <p>The <a href="https://www.niagads.org/adsp/portal/">ADSP data portal</a> provides a customized interface for users to quickly identify and retrieve files by covariates, phenotypes, and data properties such as sequencing facility or coverage. For more information about the ADSP study and the data portal, please visit <a href="https://www.niagads.org/adsp/">https://www.niagads.org/adsp/</a>.</p>
| phs000572 | dbGaP
Project description:The clinical course of Coronavirus disease 2019 (COVID-19) displays a wide variability, ranging from completely asymptomatic forms to diseases associated with severe clinical outcomes. To reduce the incidence COVID-19 severe outcomes, innovative molecular biomarkers are needed to improve the stratification of patients at the highest risk of mortality and to better customize therapeutic strategies. MicroRNAs associated with COVID-19 outcomes could allow quantifying the risk of severe outcomes and developing models for predicting outcomes, thus helping to customize the most aggressive therapeutic strategies for each patient. Here, we analyzed the circulating miRNA profiles in a set of 12 hospitalized patients with severe COVID-19, with the aim to identify miRNAs associated with in-hospital mortality.
2021-11-24 | GSE189506 | GEO
Project description:Set of 8 bam files from patients affected with Lupus. BAM alignments for exonic variants present in P2RY8 gene. VCF file describing the variants.
| EGAD00001008330 | EGA