Expanding a case vs control analysis

Question

[aj123]

Hi,

Im currently doing a simple case vs control analysis on RNA Seq data. I have WGS and SNP data as well. I was wondering what are the different layers and additional analyses I could add on to my work?

thanks!

[Kevin Blighe]

If you have obtained such data, then surely you have some hypotheses that you want to test?; or, did you just obtain some data without any hypotheses?

Here is a random mixture of ideas for you, apart from the typical differential expression analysis (RNA-seq) and association testing (WGS and SNP data):

• search for novel transcripts in the RNA-seq data
• Expression quantitative trait loci (eQTL) study (RNA-seq + WGS or RNA-seq + SNP data)
• score the variants called in the WGS data with modern prediction tools for functional impact, including CADD, DANN, FATHMM-MKL, SurfR, etc.

Aside from that, please elaborate on the exact data that you have (formats), which disease it represents, an what your hypotheses are.

[aj123]

thanks for your response! I will def try exploring these avenues. This is basically case vs control samples (bam files) I have for a human disease. Just doing a DE analyses to see DE genes of interest. Hence was trying to see what other analyses/layers I could add to this.

[Kevin Blighe]

Okay great. My list is by no means complete, of course. It's always good to get multiple ideas from multiple sources.