Ena-DATASET-GCAT-07-10-2021-15:48:18:552-38 - samples
Ontology highlight
ABSTRACT:
PROVIDER: EGAD00001008202 | EGA |
REPOSITORIES: EGA
Publications
GCAT|Genomes for life: a prospective cohort study of the genomes of Catalonia.
Obón-Santacana Mireia M Vilardell Mireia M Carreras Anna A Duran Xavier X Velasco Juan J Galván-Femenía Iván I Alonso Teresa T Puig Lluís L Sumoy Lauro L Duell Eric J EJ Perucho Manuel M Moreno Victor V de Cid Rafael R
BMJ open 20180327 3
<h4>Purpose</h4>The prevalence of chronic non-communicable diseases (NCDs) is increasing worldwide. NCDs are the leading cause of both morbidity and mortality, and it is estimated that by 2030, they will be responsible for 80% of deaths across the world. The Genomes for Life (GCAT) project is a long-term prospective cohort study that was designed to integrate and assess the role of epidemiological, genomic and epigenomic factors in the development of major chronic diseases in Catalonia, a north- ...[more]
Similar Datasets
Project description:This dataset include FASTQ files of 808 samples from GCAT cohort. Technology used HiSeq 4000, read length 150 bp, inner mate distance 300 bp. For each sample the paired -ends are generated in separated files. Each FASTQ is splitted in multiple LANEs and grouped by the Multiplex index.
| EGAD00001008201 | EGA
Project description:This dataset includes the .hap, .legend and .sample files from the GCAT|Panel (Iberian reference panel), built from 785 samples, after QC, from the 808 WGS GCAT cohort, including 30.3M SNVs, 5M Indels and 89K SVs. This resource has been generated using Shapeit4 and WhatsHap software. Technology used HiSeq 4000, read length 150 bp, inner mate disatance 300 bp.
| EGAD00010002153 | EGA
Project description:This dataset contains raw genotypes ( SNVs, Indels and SVs), from 785 samples,without applying any filter, from the 808 WGS GCAT cohort.
| EGAD00001008210 | EGA
Project description:Methods: Triplicate RNA samples from morphologically stage-matched embryos were sequenced to compare expression profiles over time. Strand-specific libraries were prepared using the TruSeq stranded total RNA-ribozero kit (Illumina) and 100-bp paired-end sequencing was performed to depth of 10 million reads per library on an Illumina HiSeq 2000. Methods: On average, 19 million 100 bp paired-end reads per library were generated. These were then adapter and quality trimmed using cutadapt and SolexaQA. Each sequencing data set was independently mapped to the zebrafish genome with a bowtie2 index generated from Danio_rerio.Zv9.70 (Ensembl) downloaded from Illumina’s iGenomes collection. Zebrafish genome danRer7was used to provide known transcript annotations from Ensembl using TopHat2 (version 2.0.9) with the following options: “tophat2 --GTF genes.gtf --library-type fr-firststrand -p 24 --mate-inner-dist -8 --mate-std-dev 6 zv9” (on average, 75.38% reads mapped uniquely to the genome). Transcriptomes were assembled with Cufflinks (version 2.2.0) using options: ‘cufflinks -p 32 --GTF genes.gtf’ and differential expression analysis between control and knockdown embryos was performed using Cuffdiff. A FDR corrected p-value of 0.05 was applied as the cut off to identify differentially regulated transcripts Results: We could show that MO assisted depletion of Rad21 and CTCF affected the transcriptional profiles of embryos in different ways.
2017-12-01 | GSE84601 | GEO
Project description:This dataset contains genotypes (35.4M of SNVs, Indels and SVs), from 785 samples, after QC filtering, from the 808 WGS GCAT cohort.
| EGAD00001007774 | EGA
Project description:Aim: We generated mice lacking Irs2 which mediates signaling pathways from insulin and IL-4 specifically in lyzM Cre expressing cells. We isolated BMDM from control and Irs2LyzM-/- mice and compared their differential gene expression under veihicle, IL-4 and LPS treatment by performing mRNA sequencing studies. Methods: BMDM from control and Irs2LyzM-/- mice were treated for 24 hours with vehicle, IL-4 (10 ng/ml) or LPS (100 ng/ml). RNA integrity was confirmed and concentration measured using a Bioanalyzer. cDNA libraries were created from up to 5 μg total RNA. There were three (Irs2LyzM-/-) and four (control) biological replicates for each group and each biological replicate was divided into eight technical replicates and sequenced on individual lanes on the Illumina HiSeq 2000 (100 bp paired-end read length) at the Sanger Institute. Raw reads from the sequenced RNAseq libraries were mapped with Tophat splice junction aligner (Kim, Pertea et al. 2013), version 2.0.8 against Ensembl mouse genome reference sequence assembly (mm9) and transcript annotations. All parameters were set to default except inner distance between mate pairs (r = 130). Gene-based read counts were then obtained using the HTSeq count module (version 0.5.4p3). Differential expression analysis was performed on the counts data using the DESeq2 Bioconductor package (version 1.16.1). The GSEA preranked tool from GSEA version 2.2.4 was used forGeneset enrichment analysis. Gene ontology enrichment analysis was also performed using the topGo Bioconductor package separately for up and down-regulated genes in the comparisons analysed ( A. Alexa, J. Rahnenfuhrer, topGO: Enrichment Analysis for Gene Ontology. R package version 2.24.0 (2016)). Results: The mRNA seq. results reveal an anti- inflammatory transcriptional profile in LPS-treated Irs2LyzM-/- BMDM compared to control BMDM. Deletion of Irs2 in BMDM under all conditions (vehicle, IL-4 and LPS) manifest alteratons in genes involved in scavenging catecholamines and supporting increased sympathetic innervation.
2019-02-14 | GSE123180 | GEO
Project description:RNA-seq is a method for mapping and quantifying the transcriptome of any organism that has a genomic DNA sequence assembly (Mortazavi et al., 2008). RNA-seq is performed by reverse-transcribing an RNA sample into cDNA, followed by high-throughput DNA sequencing, which was done here on the Illumina HiSeq sequencer. The transcriptome measurements shown on these tracks were performed on polyA selected RNA (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?term=longPolyA&type=rnaExtract) from total cellular RNA (http://hgwdev.cse.ucsc.edu/cgi-bin/hgEncodeVocab?term=cell&type=localization). PolyA-selected RNA was fragmented by magnesium-catalyzed hydrolysis and then converted into cDNA by random priming and amplified. Paired-end 2x100 bp reads were obtained from each end of a cDNA fragment. Reads were aligned to the mm9 human reference genome using TopHat (Trapnell et al., 2009), a program specifically designed to align RNA-seq reads and discover splice junctions de novo. All sequence and alignments files are available at http://hgwdev.cse.ucsc.edu/cgi-bin/hgFileUi?db=mm9&g=wgEncodeCaltechRnaSeq. Cells were grown according to the approved ENCODE cell culture protocols (http://hgwdev.cse.ucsc.edu/ENCODE/protocols/cell/mouse). Cells were lysed in RLT buffer (Qiagen RNEasy kit), and processed on RNEasy midi columns according to the manufacturer's protocol, with the inclusion of the "on-column" DNAse digestion step to remove residual genomic DNA. A quantity of 75 µgs of total RNA was selected twice with oligo-dT beads (Dynal) according to the manufacturer's protocol to isolate mRNA from each of the preparations. A quantity of 100 ngs of mRNA was then processed according to the protocol in Mortazavi et al. (2008), and prepared for sequencing on the Illumina GAIIx or HiSeq platforms according to the protocol for the ChIP-Seq DNA genomic DNA kit (Illumina). Paired-end libraries were size-selected around 200 bp (fragment length). Libraries were sequenced with the Illumina HiSeq according to the manufacturer's recommendations. Paired-end reads of 100 bp length were obtained. Reads were mapped to the reference mouse genome (version mm9 with or without the Y chromosome, depending on the sex of the cell line, and without the random chromosomes in all cases) using TopHat (version 1.3.1) (http://tophat.cbcb.umd.edu/). TopHat was used with default settings with the exception of specifying an empirically determined mean inner-mate distance and supplying known ENSEMBL version 63 splice junctions.
2012-05-09 | E-GEOD-37909 | biostudies-arrayexpress
Project description:Purpose: 224 GSM Samples form GSE32970 and GSE29692 was reanalyzed to find the TFBS-clustered regions of 133 cell lines. TFBS-clustered regions were divided into ten classes belong to the TF complexity. Methods: 1. We assigned the binding sites of 542 TFs in 133 cell lines as our record GSE53962 . 2. We performed a Gaussian kernel density estimation across the genome with a bandwidth of 300 bp, using the centers of each of the TF binding peaks as points. Then, we scanned this density for peaks, and denoted each peak a TF region.To determine the complexity of the TF region, we summed the Gaussian kernalized distance from the peak to each TF that contributed at least 0.1 to its strength. The TF region around eat peak was derived by finding the maximum distance (in bp) from the peak to a contributing TF, and then adding 150 bp (one half of the bandwidth). Each TF region is centered on the peak, and have a TF complexity value. 3. According to TFBS complexity, we divided these TFBS-clustered regions into ten classes: from TC0 to TC9 with increasing TFBS complexity. Result: Using the binding sites of 542 TFs in 133 cell lines, we assigned a TF complexity score to each TF region corresponding to the number of distinct TFs bound, resulting in ten classes TFBS-clustered regions of 133 cell lines.
2014-10-03 | GSE59016 | GEO
Project description:Background The evolution of female choice mechanisms favouring males of their own kind is considered as crucial step during the early stages of speciation. However, although the genomics of mate choice may influence both the likelihood and speed of speciation, the identity and location of genes underlying assortative mating remain largely unknown. Methods and Findings We used mate choice experiments and gene expression analysis of female D. melanogaster to examine three key components influencing speciation. We show that the 1,498 genes in Zimbabwean female Drosophila melanogaster whose expression levels differ when mating with more (Zimbabwean) versus less (Cosmopolitan strain) preferred males include many with high expression in the central nervous system and ovaries, are disproportionately X-linked and form a number of clusters with low recombination distance. Significant involvement of the brain and ovaries is consistent with the action of a combination of pre- and postcopulatory female choice mechanisms, while sex linkage and clustering of genes lead to high potential evolutionary rate and sheltering against the homogenizing effects of gene exchange between populations. Conclusion Taken together our results imply favourable genomic conditions for the evolution of reproductive isolation through mate choice in Zimbabwean D. melanogaster and suggest that mate choice may, in general, act as an even more important engine of speciation than previously realized.
2011-02-05 | GSE27076 | GEO
Project description:Purpose: 253 GSM Samples from GSE32970 and GSE29692 was reanalyzed to find the highly occupied target (HOT) regions of 154 cell lines. Methods: 1. We assigned the binding sites of 542 TFs in 154 cell lines as GSE53962 (Our last submission). 2.We performed a Gaussian kernel density estimation across the genome with a bandwidth of 300 bp, using the centers of each of the TF binding peaks as points. Then, we scanned this density for peaks, and denoted each peak a TF region(Candidate region to find HOT regions).To determine the complexity of the TF region, we summed the Gaussian kernalized distance from the peak to each TF that contributed at least 0.1 to its strength. The TF region around eat peak was derived by finding the maximum distance (in bp) from the peak to a contributing TF, and then adding 150 bp (one half of the bandwidth). Each TF region is centered on the peak, and have a TF complexity value. 3.To define HOT region according to the TF complexity, we required a complexity cutoff for each cell line.To geometrically define the cutoff we first scaled the TF complexity such that the x and y axis were from 0-1. We then found the x axis point for which a line with a slope of 1 was tangent to the curve. We define this point as the cutoff value,TF region whose complexity above this point to be HOT region, and TF region complexity below that point to be lowly occupied target (LOT) regions. Result: Using the binding sites of 542 TFs in 145 cell lines, we assigned a TF complexity score to each TF region corresponding to the number of distinct TFs bound, resulting in HOT regions of 145 cell lines.
2015-01-14 | GSE54296 | GEO