|
| Status |
Public on Dec 29, 2019 |
| Title |
Rseq_S1 |
| Sample type |
SRA |
| |
|
| Source name |
peripheral blood mononuclear cells (PBMC)
|
| Organism |
Homo sapiens |
| Characteristics |
condition: Control
|
| Treatment protocol |
Cryobanked peripheral blood mononuclear cells (PBMC) were thawed and cultured in AIM-V medium (Gibco) with 50 μg/ml polyI:C extract (Invivogen), or medium alone (control) in triplicate. After 24 h, cells were harvested and total RNA was extracted.
|
| Extracted molecule |
total RNA |
| Extraction protocol |
total RNA was extracted using TRIzol (Invitrogen) followed by purification on an RNeasy column (Qiagen)
mRNA libraries were prepared at the Ramaciotti Centre for Genomics (UNSW University of New South Wales, Australia). The Illumina TruSeq Stranded mRNA Prep Kit was used .The six RNA-Seq libraries were sequenced using the Illumina NextSeq 500. R1.fastq and R2.fastq files were produced for each sample.
QuantSeq libraries were prepare using Lexogen’s QuantSeq 3’ mRNA-Seq Library Prep Kit for Illumina, according to the manufacturer’s instructions.
QuantSeq libraries were sequenced using the Illumina NextSeq 500 to produce 75 bp single-end reads for each sample
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NextSeq 500 |
| |
|
| Description |
RNA-Seq library ~ 92 M reads per sample
Rseq_counts.txt, RseqSal_counts.txt
|
| Data processing |
RNA-Seq and QuantSeq reads (fastq files) were mapped to the Ensembl Homo sapiens genome (GRCh38). Mapping was performed with Tophat2 (v 2.0.12) (Langmead and Salzberg 2012) calling Bowtie2 (v 2.2.3) (Kim et al. 2013)
The featureCounts function of Subread (v 1.4.6-p5) (Liao et al. 2014) was used to generate counts of reads uniquely mapped to annotated genes using the GRCh38 gtf file.
The table of read counts was used as input to assess differential expression using the Bioconductor packages, edgeR and limma (voom).
The abundance quantification method Salmon (Patro et al. 2017) to calculate transcript abundance based on the transcript fasta files downloaded from ensemble-release87, (Homo_sapiens.GRCh38.cdna.all.fa and Homo_sapiens.GRCh38.ncrna.all.fa)
The Bioconductor package tximport (Soneson et al. 2015) was used to convert transcripts to gene counts which could be used in downstream differential expression analysis.
The table of read counts was used as input to assess differential expression using the Bioconductor packages, edgeR and limma (voom).
Genome_build: Ensembl Homo sapiens genome (GRCh38).
Supplementary_files_format_and_content: Tab-delimited text file with read count for each sample.
|
| |
|
| Submission date |
Dec 09, 2018 |
| Last update date |
Dec 29, 2019 |
| Contact name |
Susan Corley |
| E-mail(s) |
s.corley@unsw.edu.au
|
| Phone |
+61 02 9385 8853
|
| Organization name |
UNSW
|
| Department |
Biotechnology & Biomolecular Sciences
|
| Lab |
Systems Biology Initiative
|
| Street address |
D26, Kensignton Campus
|
| City |
Sydney |
| State/province |
NSW |
| ZIP/Postal code |
2052 |
| Country |
Australia |
| |
|
| Platform ID |
GPL18573 |
| Series (1) |
| GSE123523 |
Comparing transcriptomic analysis using QuantSeq and RNA-Seq with Salmon quantification and Tophat2 mapping |
|
| Relations |
| BioSample |
SAMN10536693 |
| SRA |
SRX5123063 |
