Question: Methods to interrogate RNA-seq
0
gravatar for telroyjatter
3 months ago by
telroyjatter160
telroyjatter160 wrote:

Let's say you have an RNA-seq counts matrix for two experimental groups, and you have already generated your table of differentially expressed genes. Generally speaking, what are the best ways to interrogate this dataset?

The ones I can think of:

  • Gene ontology enrichment
  • WGCNA and/or MEGENA for co-expression networks: modules; eigengenes, eigengene networks
  • ARACNE for transcription factor-target networks
  • Key driver analysis (i.e., which hub gene in WGCNA/MEGENA/ARACNE has the highest connectivity; what other ways are there to define key drivers?)
  • HOMER for regulatory binding sites

Any other methods, reviews, papers are highly appreciated!

rna-seq • 310 views
ADD COMMENTlink modified 10 weeks ago • written 3 months ago by telroyjatter160
1

The first thing is "what is your biological question?" Every analysis depends on that response.

ADD REPLYlink written 3 months ago by JC12k

Let's say the tissue is from brain, and we want to understand how the administration of a drug affects gene expression.

ADD REPLYlink written 3 months ago by telroyjatter160

already generated ... table of differentially expressed genes

So you have a list of genes and are looking for biological meaning in this list?

ADD REPLYlink written 3 months ago by _r_am32k

Or in the entire dataset, for example some methods include an entire counts matrix rather than just a list of DEGs or the counts of only DEGs.

ADD REPLYlink written 3 months ago by telroyjatter160

Echoing JC here: if you're only thinking of a question after having generated the data, things have been done backwards.

Why is the list of methods you've listed not sufficient to get you started?

ADD REPLYlink written 3 months ago by Friederike6.7k

It is enough to get started. I don't even have data. I just want to create a list of all of the methods, with their respective applications, that can be used to mine, interrogate, and extract knowledge from an RNA-seq dataset (or *omics datasets more generally).

ADD REPLYlink written 3 months ago by telroyjatter160

If my biological question is to understand how a drug affects the transcriptome, are there tools or a particular workflow that would be recommended?

ADD REPLYlink written 10 weeks ago by telroyjatter160
2
gravatar for Kevin Blighe
3 months ago by
Kevin Blighe69k
Republic of Ireland
Kevin Blighe69k wrote:

Perhaps you can obtain some insight from my answer, here: What is the best way to combine machine learning algorithms for feature selection such as Variable importance in Random Forest with differential expression analysis?

Kevin

ADD COMMENTlink written 3 months ago by Kevin Blighe69k
1

Yes this is helpful. Thanks, Kevin!

ADD REPLYlink written 3 months ago by telroyjatter160
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