Question: using paired end and single end data in featurecounts
gravatar for nikelle.petrillo
16 months ago by
nikelle.petrillo0 wrote:

Hi all, 

I have 4 .sam files after aligning. 3 of the SAM files were created from PE data, and 1 SAM file was created from SE data. I want to use featurecounts to create a count matrix, however, should I be using paired end mode or single end mode? 

Thanks for the help, 


ADD COMMENTlink modified 16 months ago by James W. MacDonald48k • written 16 months ago by nikelle.petrillo0

hi, I'm gonna remove the deseq2 tag, as it's a featureCounts question.

ADD REPLYlink written 16 months ago by Michael Love20k
gravatar for James W. MacDonald
16 months ago by
United States
James W. MacDonald48k wrote:

Presumably you aligned the PE data by telling your aligner that it was PE, and the SE was aligned in SE mode, correct? In that case you should probably use featureCounts in PE mode for the PE data and in SE mode for the SE data. I don't know what featureCounts will do if you give it PE aligned data and say it is SE (double count the paired reads?), but pretending the PE data are SE is probably not the way to go.

ADD COMMENTlink written 16 months ago by James W. MacDonald48k

Thanks James. Yes, the PE data was aligned as PE and the SE data was aligned as SE. I would like to create 1 count matrix made from all 4 .sam files using featureCounts. Are you saying to create a count matrix for the 3 .sam files (PE data, using PE mode in feautreCounts) and a separate count matrix for the 1 .sam file (SE data, using SE mode in feautreCounts)? 

If so, is there then a way to combine these 2 count matrices into 1? 


ADD REPLYlink written 16 months ago by nikelle.petrillo0

Of course! That's just a basic R data manipulation step. From ?featureCounts


     A list with the following components:

  counts: a data matrix containing read counts for each feature or
          meta-feature for each library.

So the output will be a list, the first item being a matrix with the read counts. You can then just cbind the two counts matrices (ensuring of course that the rows line up correctly) and go from there.

ADD REPLYlink written 16 months ago by James W. MacDonald48k

Or merge in R would work as well. But I would remove the chromosom, start, end, strand and length column in the two dfs.

new_df <- merge(table1_df, table2_df, by.x = 'Geneid', by.y = 'Geneid')
ADD REPLYlink written 16 months ago by mat.lesche70
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