RNAseq analysis: I have read counts for all CDS. Could I use standard methods (limma-voom, edgeR) for DEA??
Hi all,
I have read counts for all the cds in the new version of the human genome. The mapping was done to the genome and then, the counts were calculated using cds. I was wondering if I could use standard methods for doing Differential Expression Analysis. Could you point me to some references?
Thank you in advance!
0 answers
No answers yet.
Log in to answer this question.
More posts like this
-
using non-matched read counts for differential expression analysis (ncRNA)?
written by danazeid3 •
-
Not removing biological contaminants from transcriptome - consequences?
written by tanya_fiskur •
-
Feature selected-genes vs. differentially expressed genes
written by randalljellis
-
How can I get Ensembl CDS / 3'UTR and 5'UTR sequences
written by 2405592M
-
Human brain samples (BAM files) differential gene expression
written by nermze86 •
-
Mapping short 26-32nt RPF reads to human genome
written by Adrian Pelin
-
TCGA RNAseq Data is normalized against which Genome version
written by rajesh
-
Analysis of GEO dataset normalized by FPKM
written by GSAENZDEPIP •
-
multi-mapped reads counting methods with RNA-seq
written by guillaume.rbt
-
High p-values generated from CuffDiff
written by onspotproductions
That's a bit unusual. CDS is not precise as large parts of a given CDS can be shared among transcripts of the same genes. Can you say what precisely the setup is? It would likely be better/more standard/more reliable to simply quantify your data against the entire transcriptome.