I am about to undertake RNA-Seq analysis to assess the lncRNA expression induced in viral infected human cells.
Experimental Conditions: I have three conditions that I need to test; wildtype virus infected, mutant virus infected, and uninfected.
I am able to analyse data up to and including differential expression using DESeq2 but i do wish to assess the relationships between differentially expressed human lncRNA and mRNA. The annotation that i use is from GENCODE (Human Primary Assembly) supplemented with lncRNA annotation from LNCipedia.
I have never done co-expression or network analysis before and i am slightly confused as to how to correlate lncRNA expression with that of mRNA expression. I am aware of the R/Bioconductor Package, WGNCA and have attempted to use it with log2 normalized raw counts generated from HTSeq. However, i am not sure as to how to use the result from WGNCA to assess lncRNA and mRNA relationships.
In my last RNA-Seq experiments I used an unstranded NGS library generated from 9 samples (3 replicates per condition as mentioned above) in my analysis, but i am having difficulty in determining some lncRNA gene expression especially those located at intronic and antisense positions. One suggestion was to use a stranded library for future analysis for these lncRNA gene types, though i am unsure.
- What criteria should i select in NGS library preparation to best assess lncRNA differential expression but also to allow for co-expression analysis of lncRNA with mRNA? (strandedness, number of samples, etc)
- The raw counts generated from HTSeq include both lncRNA genes and protein coding genes using the above annotation. For DESeq2 analysis would it be of any benefit to extract lncRNA genes from the raw-count data and process them separately rather than process everything together through DESeq2 /WGNCA?
Any feedback would be most appreciated. Thanks.