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From the abstract, a brief description of the RNA-Seq experiment on airway smooth muscle (ASM) cell lines: “Using RNA-Seq, a high-throughput sequencing method, we characterized transcriptomic changes in four primary human ASM cell lines that were treated with dexamethasone - a potent synthetic glucocorticoid (1 micromolar for 18 hours).”
Data source:
NCBI - Short Read Archive
https://www.ncbi.nlm.nih.gov/bioproject/PRJNA229998
Sample information
| Code Block |
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## SampleName cell dex Run
## SRR1039508 GSM1275862 tissue: human airway smooth muscle cells untrt SRR1039508
## SRR1039509 GSM1275863 tissue: human airway smooth muscle cells untrt SRR1039509
## SRR1039510 GSM1275864 tissue: human airway smooth muscle cells untrt SRR1039510
## SRR1039511 GSM1275865 tissue: human airway smooth muscle cells untrt SRR1039511
## SRR1039512 GSM1275866 tissue: human airway smooth muscle cells untrt SRR1039512
## SRR1039513 GSM1275867 tissue: human airway smooth muscle cells untrt SRR1039513
## SRR1039514 GSM1275868 tissue: human airway smooth muscle cells untrt SRR1039514
## SRR1039515 GSM1275869 tissue: human airway smooth muscle cells untrt SRR1039515
## SRR1039516 GSM1275870 tissue: human airway smooth muscle cells untrt SRR1039516
## SRR1039517 GSM1275871 tissue: human airway smooth muscle cells untrt SRR1039517
## SRR1039518 GSM1275872 tissue: human airway smooth muscle cells untrt SRR1039518
## SRR1039519 GSM1275873 tissue: human airway smooth muscle cells untrt SRR1039519
## SRR1039520 GSM1275874 tissue: human airway smooth muscle cells untrt SRR1039520
## SRR1039521 GSM1275875 tissue: human airway smooth muscle cells untrt SRR1039521
## SRR1039522 GSM1275876 tissue: human airway smooth muscle cells untrt SRR1039522
## SRR1039523 GSM1275877 tissue: human airway smooth muscle cells untrt SRR1039523
## avgLength Experiment Sample BioSample
## SRR1039508 126 SRX384345 SRS508568 SAMN02422669
## SRR1039509 126 SRX384346 SRS508567 SAMN02422675
## SRR1039510 126 SRX384347 SRS508570 SAMN02422668
## SRR1039511 126 SRX384348 SRS508569 SAMN02422667
## SRR1039512 126 SRX384349 SRS508571 SAMN02422678
## SRR1039513 87 SRX384350 SRS508572 SAMN02422670
## SRR1039514 126 SRX384351 SRS508574 SAMN02422681
## SRR1039515 114 SRX384352 SRS508573 SAMN02422671
## SRR1039516 120 SRX384353 SRS508575 SAMN02422682
## SRR1039517 126 SRX384354 SRS508576 SAMN02422673
## SRR1039518 126 SRX384355 SRS508578 SAMN02422679
## SRR1039519 107 SRX384356 SRS508577 SAMN02422672
## SRR1039520 101 SRX384357 SRS508579 SAMN02422683
## SRR1039521 98 SRX384358 SRS508580 SAMN02422677
## SRR1039522 125 SRX384359 SRS508582 SAMN02422680
## SRR1039523 126 SRX384360 SRS508581 SAMN02422674 |
metadata information (metadata.txt):
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Run SampleName cell group
SRR1039508 GSM1275862 N61311 control
SRR1039509 GSM1275863 N61311 dex
SRR1039512 GSM1275866 N052611 control
SRR1039513 GSM1275867 N052611 dex
SRR1039516 GSM1275870 N080611 control
SRR1039517 GSM1275871 N080611 dex
SRR1039520 GSM1275874 N061011 control
SRR1039521 GSM1275875 N061011 dex |
dex= dexamethasone treatment
Downloading data
Prior to downloading the data, first, we need to install the NCBI’s sra-tools using conda:
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conda install -c bioconda sra-tools |
The prepare a list of SRR accession numbers of interest to fetch FASTQ data:
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cat metadata.txt | awk '{print $1}' | sed 1d > SraAccList.txt |
Check SraAccList.txt (i.e., cat SraAccList.txt):
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SRR1039508
SRR1039509
SRR1039512
SRR1039513
SRR1039516
SRR1039517
SRR1039520
SRR1039521 |
Once the list of wanted SRA accession IDs is ready, use a PBS Pro submission script to fetch all the sequences. Note, data will be downloaded to the folder where the job is submitted. Example script (fetch_SraAccList.pbs):
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#!/bin/bash -l
#PBS -N sra_fetch
#PBS -l walltime=8:00:00
#PBS -l mem=8gb
#PBS -l ncpus=4
#PBS -m bae
###PBS -M email@host
#PBS -j oe
#Usage: qsub fetch_SraAccList.pbs
cd $PBS_O_WORKDIR
for i in `cat SraAccList.txt`;
do
echo $i
prefetch $i
fastq-dump --split-files $i
done |
Pre-processing of public data
Downloaded public data for the airway smooth muscle project show size differences between ‘Read 1’ and ‘Read 2’ FASTQ files. Prior to running the nextflow nf-core/RNAseq pipeline, downloaded raw data will be quality checked using default trim galore options:
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#!/bin/bash -l
#PBS -N QC_P1-6
#PBS -l walltime=2:00:00
#PBS -l mem=8gb
#PBS -l ncpus=4
#PBS -m bae
#PBS -M email@host
#PBS -j oe
#User-defined parameters:
SAMPLEID=SRR1039513
READ1=SRR1039513_1.fastq
READ2=SRR1039513_2.fastq
#Pipeline:
cd $PBS_O_WORKDIR
#make output folder
mkdir -p trimgalore
# Remove adaptors and poor quality bases/reads using trimgalore. Minimal quality score of 20 (-q20) and minimal length of 50 bases (--length 50)
trim_galore --length 50 --cores 4 --paired -q 20 --fastqc -o ./trimgalore ${READ1} ${READ2} |