We use featureCounts to generate raw counts for RNA-Seq data. The raw counts are then normalized for sequencing depth and gene length. The raw counts are used as input for the differential expression analysis. We currently edgeR for differential expression analysis.
Transcript assembly and expression
The raw counts for each of the sample are used in our edgeR analysis for differential expression and to output normalized TPM (Transcript perm million) values for both the GENCODE and igenomes classifications.
Differential expression analysis is carried out by edgeR (using both the igenomes GTF and the GENCODE GTFs). The edgeR analysis produces fold change smear plots, tagwise dispersion plots, cluster plots, mean variance plots, normalized counts and most importantly a table of differentially expressed genes/transcripts. The different outputs are described more in detail in this edgeR user guide.
Normalization in RNA sequencing
Raw counts are normalized for sequencing depth, gene length and also to account for variation (technical/biological) in the libraries. We provide users with TPM counts (Transcript per million). For details about various types of normalization apllied to RNA sequencing dataset please visit the link.