Question: GSEA with variant proportions as input
0
gravatar for manali.rupji
3.7 years ago by
United States
manali.rupji0 wrote:

Hello All,

I am interested in using using variant proportions as input to perform Gene Set Enrichment Analysis (GSEA). Is anyone aware of a Bioconductor package in R or any other tool that can help me do GSEA analysis using variant proportions data as input rather than the typical RNA seq expression data. I have two different phenotype groups which I want to compare and I can have the proportion data transformed if needed. I also intend to combine these results with RNA seq expression data results.

Doing some research, I have come across many papers using p values but I am mainly interested in using variant data input.

Any help would be greatly appreciated. Thanks,

M

ADD COMMENTlink modified 6 months ago by Biostar ♦♦ 20 • written 3.7 years ago by manali.rupji0
1

What kind of data you have ? Tell more about the experiment. Can you give some examples like whats there in rows and columns ? You could try GSEA Pre-Ranked Analysis if you can rank your data somehow. But if you can give more information, people could help.

ADD REPLYlink written 3.7 years ago by geek_y9.4k

In addition to the comment from Goutham Atla, you'll need to carefully consider how you normalize for any apparent GC composition bias or other large coverage differences between samples (since these might affect the variant calling power and lead to aberrant proportion measures). Some of the functions from deepTools might come in handy here (not that I want to intentionally plug some tools from a colleague).

ADD REPLYlink written 3.7 years ago by Devon Ryan89k
0
gravatar for vassialk
3.7 years ago by
vassialk190
Belarus
vassialk190 wrote:

For WGS I use NextGene software. It is the best. For the microarrays --- Expander, MeV and Genesis softwares. If you like to suffer and lose time, you can use Ugene, CLC, VCF tools, GATK, R, and end up with writing your own C++ and Assembler library for that purpose
 

ADD COMMENTlink written 3.7 years ago by vassialk190
2

Err, you use commercial products like NextGene if you can afford to be 1-3 years behind the rest of the field in doing analyses. Your reply also bears no relation to the actual question posed...

ADD REPLYlink written 3.7 years ago by Devon Ryan89k

Thank you Vassialk for the information! I am relatively new to performing such analyses. What is the tool of choice for RNAseq data? Is there any Bioconductor package that may be of help?

 

ADD REPLYlink written 3.7 years ago by manali.rupji0
0
gravatar for vassialk
3.7 years ago by
vassialk190
Belarus
vassialk190 wrote:

What you want to do with your data? R with Bioconductor and Python/Ruby/Java are good for short reads and some microarrays (R limma). When you have to dig a whole genome of a microbe or a mammal  they are not easy to apply and almost no use from them if your goal is not to build your own software and you have a limited time of the research project. However, BioPython and BioRuby functions are easy to incorporate into your Qt/GTK/Wx software or into the website with a data processing functionality. There is no rational need to rewrite these useful functions.

ADD COMMENTlink written 3.7 years ago by vassialk190
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