Ontology highlight
ABSTRACT:
PROVIDER: PRJNA744329 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR15058164_1.fastq.gz | Fastqsanger.gz | |||
| SRR15058165.fastq.gz | Fastqsanger.gz | |||
| SRR15058166_1.fastq.gz | Fastqsanger.gz | |||
| SRR15058167_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 4 of 4 |
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Project description:Intervention type:DRUG. Intervention1:Huaier, Dose form:GRANULES, Route of administration:ORAL, intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary. Control intervention1:None.
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2011-07-01 | GSE27697 | GEO
Project description:S2 cells were infected with FHV deltaB2 particle and the S2 cells were harvested to isolate total RNA at 96 hpi. Small RNAs were separated on a denaturing 15% polyacrylamide gel. Ligation to adapters requires 5' monophosphate and 3' OH. Note: The base quality (.qual) file corresponding to the fasta format (.fna) file linked to Sample GSM306489 is unavailable.
2008-10-16 | GSE12527 | GEO
Project description:Temporal analysis of Irf4 and PU.1 genome binding during B cell activation and differentiation in vitro using antigen (NP-Ficoll) CD40L and IL-2/4/5 cytokines (see Molecular Systems Biology 7:495 for details of cellular system). The results provide insight in the target genes and binding specificity of IRF4 and PU.1 during coordination of different programs of B cell differentiation. Regrettably three of the FASTQ raw sequence files in our study were corrupted during storage. FASTQ data from our experimental and control groups are available for download via GEO SRA; however, two groups are missing select raw sequence files. These include one PU.1 Day 3 group file (Sample GSM1133499) and two of four input files used to generate a concatenated “super” input file (Sample GSM1133490); the raw data provided for input consists of the two input files recovered. Importantly, FASTA sequences for both of these datasets are available as supplementary data through GEO, and we can make available upon request (rsciamma@uchicago.edu) all files in our study in the ELAND-extended alignment format. Please note that GEO no longer supports this format.
2013-05-04 | GSE46607 | GEO
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Project description:Intervention type:DRUG
Name of intervention:Huaier
Dose form / Japanese Medical Device Nomenclature:GRANULES
Route of administration / Site of application:ORAL
Dose per administration:20?
g
Dosing frequency / Frequency of use:OTHER, SPECIFY
20g? per day
Planned duration of intervention:3 months to extending if necessary
Intended dose regimen:20 to 60/day by either bulk or split for 3 months to extended term if necessary
detailes of teratment arms:hepatocellular carcinoma, breast cancer, colorectal cancer and related gastrointestinal cancers, urologic cancers including prostate cancer, pancreas cancer, and lung cancer, etc.
Comparative intervention name:None
Dose form / Japanese Medical Device Nomenclature:
Route of administration / Site of application:
Dose per administration:
Dosing frequency / Frequency of use:
Planned duration of intervention:
Intended dose regimen:
Primary outcome(s): For mRNA libraries, focus on mRNA studies. Data analysis includes sequencing data processing and basic sequencing data quality control, prediction of new transcripts, differential expression analysis of genes. Gene Ontology (GO) and the KEGG pathway database are used for annotation and enrichment analysis of up-regulated genes and down-regulated genes.
For small RNA libraries, data analysis includes sequencing data process and sequencing data process QC, small RNA distribution across the genome, rRNA, tRNA, alignment with snRNA and snoRNA, construction of known miRNA expression pattern, prediction New miRNA and Study of their secondary structure Based on the expression pattern of miRNA, we perform not only GO / KEGG annotation and enrichment, but also different expression analysis.
Study Design: Comparative test, None, No, open(masking not used), EXPLORATORY
| 98681 | ecrin-mdr-crc
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