Hi All,
I am new to DESeq2 analysis and I follow the trinity pipeline for DESeq2 analysis. In that pipeline, RSEM is used to quantify the transcript abundance which generates the expected counts. These expected counts will be rounded off and later fed into DESeq2 pipeline for further analysis.
I would like to know whether these expected counts generated from RSEM can be fed into DESeq2 instead of raw counts for computing differential expressed genes?
Regards
Chudar
Hi! I must import RSEM data to DESeq2 for downstream analyses. My RSEM output has the following columns:
gene_id transcript_id(s) length effective_length expected_count TPM FPKM
I tried to follow the tximport tutorial from
https://bioconductor.org/packages/release/bioc/vignettes/tximport/inst/doc/tximport.html
but I got the following error:
My code is as follows:
Do you have any suggestions?
Thanks!
See here:
Using RSEM with tximport and DESeq2
Thanks a lot for the helpful reply; adding
before
has apparently solved the problem.
BTW, is it possible to import into DESeq2 rsem data and combine them with data from featureCounts in order build a merged matrix with normalized counts? - Thanks!
That is not trivial I would say, you would need to correct for / model the differences in quantification method somehow. I haven't attempted this.