Alternative splicing analysis of targeted RNASeq data

Question

[ddzhangzz]

My client has run targeted RNA sequencing for a list of genes from different chromosomes in human and wanted to perform alternative splicing analysis. I have never been working on these type of targeted data analysis and am wondering whether there is standard ways for this analysis. What programs I can use to do this analysis? Could somebody can give me some possible description of the procedure?

Answer 1

[EagleEye]

Check out previous posts

A: workflow/tool for alternative splicing

Or if your are newbie try this workflow,

Are those total RNA (Transcriptome) sequencing samples? If so,

try,

Tools:

1) FastQC (Check quality of sequencing).

2) Trimmomatic or Cutadapt (if necessary, uncleaned reads for adapters)

3) STAR or HISAT2 (I would personally recommend STAR)

4) SAMstat (Check quality of alignment)

5) RSEM or Cufflinks (Check mapping quality, MAPQ using SAMstat from alignment before starting quantification)

6) Differential expression analysis: DESeq2 or edgeR or Ballgown (I personally not tried ballgown)

7) GeneSCF v1.1 (command-line)/Enrichr (Web-based) [Gene ontology or pathway analysis for differentially expressed isoforms related genes, this step is only applicable for protein coding genes]. GeneSCF is more reliable than other tools because it is real-time based and also check other advantages of using GeneSCF.

[WouterDeCoster]

Given that OP is talking about targeted RNA-seq data (which I interpret as including a probe-based capture step in library prep) I expect that assumptions made in common differential expression analysis tools are violated, e.g. DESeq2 and edgeR expecting most genes to be not differentially expressed for dispersion estimation.

[Santhilal Subhash (EagleEye)]

If this is RNA Capture-seq, the 6th step is not necessary as mentioned by WouterDeCoster. Also check this article.

[ddzhangzz]

Thanks to @EagleEye. but what I am interested is how to do it for targeted RNASeq data in AS analysis (for selected genes).