If we have a list of differential proteins from proteome data-sets, should we use all the differential genes together while running the analysis? Or, should those be run separately?
Additionally, which is/are the currently reliable tool(s) for Ontology or Enrichment analysis for proteome data-sets.?
Hi Divyank,
There is not a book answer for that and it depends on what are you actually interested in studying and what kind of question you want to answer. As Ajit said you can focus in all the DEGs, the up or down regulated and if you are comparing between two or more conditions you can also studying the ones correlated in the same or opposite sense of regulation... In the end it depends on :
1. What is your question.
2. What is your experimental setup, samples to study and the specific contrasts that you want to assess.
3. The kind of differential functional analysis you want to carry on: Singular Enrichment Analysis (SEA), Gene Set Enrichment Analysis (GSEA) ...
4. Which ifnormation you have in your proteomic input data. About the methology and tools to use maybe you will find this paper useful Article Pathway and Network Analysis in Proteomics
Best,
Hi Divyank,
This is a good question, and you're certainly not the first one to ask this.
See these discussions on biostars:
https://www.biostars.org/p/100123/
https://www.biostars.org/p/155501/
And these two papers:
http://rsif.royalsocietypublishing.org/content/11/92/20130950.short?rss=1
https://peerj.com/articles/159/
You could also circumvent the problem by looking for enrichment of absolute values of fold changes, or by just looking at the p-values.
Good luck!
Rik
Thanks Ajit.
Thanks Mar; Those were important points to consider.
Thank you Rik; That's really helpful!. Going through these links.
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