Question: RNA_Seq Data Analyse
0
gravatar for Diango
11 months ago by
Diango0
Bamako
Diango0 wrote:

hello everybady , I'm new in rnaseq data analyse and I need to do the transcriptomic profiling between two biological conditions (wildtype and mutant) follow this plan : QC ---> indexation and mapping with STAR ----> quantication with featurecount ----> and now I would like to analyse the the featurecount.txt output in R using edgeR.

EdgeR dataset : in each featurecount output.txt I use this linux commande to :

1. cut -f1 featurecount.txt > gene_id.txt #extraire the first column called gene_id
2. cut -f7 featurecount.txt > file.txt # for each sample
3. paste gene_id file.txt(for each sample) > count.txt

I export the count.txt in using edgeR package following this script:

library(edgeR)
## Loading required package: limma
library(limma)
library(Glimma)
library(gplots)
## Attaching package: 'gplots'

library(dplyr)
#library(org.Mm.eg.db
#library(RColorBrewer
options(width = 100)

setwd("C:/Users/DIANGO/Desktop/GNF_Matrix")
wt1 <- read.delim("./GWT_vs_B6.txt", stringsAsFactors = FALSE, comment.char = "#")
dim(wt1)

## Create a new data object that contains just the counts.

countdata <- wt1[,7, drop = FALSE]
head(countdata)
dim(countdata)

## Add rownames i.e. GeneIDs to data
rownames(countdata) <- wt1[,1]
head(countdata)


# Taking a look at column names to know the sample names
colnames(countdata)

## [1] "X.data.cephfs.punim0010.projects.Kanwal_RNASeq_Testing.seqc.test.rna.seq.work.kallisto.RNA.Test.kallisto.pseudoalignment.pseudoalignments.sorted.bam"

#Renames sample name to a meaningful title
colnames(countdata) <- "WILD1"
head(countdata)

if there's anyone who can help me with this analysis or suggest other methods.

rna-seq R gene • 305 views
ADD COMMENTlink modified 10 months ago by brianj.park50 • written 11 months ago by Diango0

Please edit your question to re-format the code. Essentially, highlight your code chunks and then click on the 101 010 button. Thanks.

ADD REPLYlink written 11 months ago by Kevin Blighe69k

My questions is juste focus to how analysis featurecount output file with edgeR or DESeq2 R package. thk @kevin for your clarification

ADD REPLYlink written 11 months ago by Diango0

What is unclear after reading the manual from edgeR? It involves all code for a standard analysis.

ADD REPLYlink written 11 months ago by ATpoint44k
1
gravatar for brianj.park
10 months ago by
brianj.park50
Montréal, Canada
brianj.park50 wrote:

After you imported your count table into R, you have to create a DGEList object that contains your counts, gene IDs, and sample group info needed for differential expression. Follow this vigenette and it should be straightforward.

ADD COMMENTlink written 10 months ago by brianj.park50

thank you very much brian j.park I'm doing great with your link

ADD REPLYlink written 10 months ago by Diango0
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