Skip to content
Branch: master
Find file History
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
..
Failed to load latest commit information.
figures
.DS_Store
.Rapp.history
2014-RNA-seq-GSE52778.pdf
DEG_results.Rdata
DEG_rnsseq.R
SRR_Acc_List.txt
SraRunTable.txt
airway.Rproj
airway_exprSet.Rdata
functions.R
readme.md
rnaseq-workflow.txt

readme.md

A brief example for RNA-seq data analysis

Firstly you should read the paper more than 3 times.

PLoS One. 2014 Jun 13;9(6):e99625. doi: 10.1371/journal.pone.0099625. eCollection 2014.

RNA-Seq transcriptome profiling identifies CRISPLD2 as a glucocorticoid responsive gene that modulates cytokine function in airway smooth muscle cells.

In that paper, we can find the raw data of this experiment, which is located in : https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE52778

If you are familar with RNA-seq workflow , you can process those data from begin to end, get the expression matrix by your self, but you can also load the expression matrix by R package: airway

The readme for this package: https://bioconductor.org/packages/release/data/experiment/vignettes/airway/inst/doc/airway.html

check the correlation of expression matrix

As we can see, the samples in same group are more similar with each other than samples in different group.

DEG script

It's very easy to understand, so I don't want to explain the codes one by one.

You can also read my tutorial rnaseq-workflow.txt to study how to process the raw fastq data of RNA-seq.

The R code : DEG_rnsseq.R

annotation

Once we get the DEG list, we can annotate those genes.

You can’t perform that action at this time.