|
| Status |
Public on Jan 15, 2022 |
| Title |
mitral valve endothelial cells (VECs) treated with post-MI plasma rep2 |
| Sample type |
SRA |
| |
|
| Source name |
Mitral valve endothelial cells (VECs)
|
| Organism |
Ovis aries |
| Characteristics |
treatment: ovine post-MI plasma treated
|
| Extracted molecule |
total RNA |
| Extraction protocol |
library preparation was performed using the TruSeq Stranded mRNA LT Sample Prep Kit (Illumina Inc., Part# 15031047). Sequencing was performed on the Illumina HiSeq 2000 (paired-end 150 bp) using the TruSeq SBS Kit v3-HS (Illumina Inc.).
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina HiSeq 2000 |
| |
|
| Data processing |
Aligning reads using STAR (v2.5.2b) was performed in two steps: (i) creating genome indices using Ovis_aries.Oar_v3.1 genome assembly (GCA_000298735.1) and Ovis_aries.Oar_v3.1.99.gtf annotation. We obtained thereference genome and the reference annotation for the sheep from the Ensembl database. (ii) read alignment.
The alignments of fastq files produced random order with respect to their position in the reference genome. The BAM files therefore were sorted using Samtools
Assessing alignment quality and mapping statistics were performed by ready Log.final.out files and uniquely mapped read, reads that mapped to mutliple locations and reads that were unmapped were defined. In addition to the STAR-specific summary we also obtain quality metrics using Qualimap and RNA-SeQC.
To perform subsetting and visualization of the alignment using a genome browser on the BAM file, an index was generated using Samtools (v1.9) and Integrative Genomics Viewer (IGV) was used to assess the quality of the alignment.
The counts of reads that were mapped to a single location (uniquely mapping) were used as an input for featureCounts (v2.0.0) tool to get the gene counts
featureCounts output file (count matrix) was then used to extract the read count, genomic coordinates and the length of the gene. Finally, multiQC (v1.5) was run on the files from (i) FastQC, .(ii) Log.final.out files from STAR and (iii) .summary file from featurecounts outputs from our workflow. This enabled us to aggregate the results from several tools and generates a single HTML report with plots to visualize and compare various QC metrics between the samples.
DESeq2 (v1.26.0) was used for estimation of variance-mean dependence in count data and test for differential expression based on a model using the negative binomial distribution.The DESeq2 package was run using R program (Bioconductor version: Release (3.10)).
Genome_build: GCA_000298735.1
Supplementary_files_format_and_content: Matrix table with raw gene counts for every gene and every sample
|
| |
|
| Submission date |
Aug 24, 2021 |
| Last update date |
Jan 15, 2022 |
| Contact name |
Ali Hashemi Gheinani |
| E-mail(s) |
ali.hashemigheinani@childrens.harvard.edu
|
| Organization name |
Boston Children's Hospital
|
| Department |
Urology
|
| Street address |
300 Longwood
|
| City |
Boston |
| ZIP/Postal code |
02215 |
| Country |
USA |
| |
|
| Platform ID |
GPL15670 |
| Series (1) |
| GSE182696 |
The Wnt inhibitor sFRP3 protects mitral valve endothelium from MI-induced EndMT |
|
| Relations |
| BioSample |
SAMN20962958 |
| SRA |
SRX11897750 |
