Is it possible to do enrichment analysis for selected genes just with GO number in topGO?
2
0
Entering edit mode
6.3 years ago
ThulasiS ▴ 90

I would like to get Fisher's exact Test, FDR value for certain selected genes. But later i understood that can be done only if we have expression data along with GO number. But in one article they did without any expression data. I am confused, really is it possible to carry gene enrichment analysis for some recombinant genes of bacterial gene. If possible how to do. Please explain me.

Thank you

R Enrichment Analysis • 2.0k views
ADD COMMENT
0
Entering edit mode

Are you looking for Blast2GO ?

"Blast2GO offers the possibility of direct statistical analysis on gene function information. A common analysis is the statistical assessment of GO term enrichment in a group of interesting genes when compared to a reference group i.e. to asses the functional differences between two sets of functional annotations (e.g. GO function of two groups of genes). This analysis is typically performed by a Fisher's Exact Test in combination with a robust False Discovery Rate (FDR) correction for multiple testing." Source: https://biobam.atlassian.net/wiki/spaces/BFCD/pages/5668926/Fisher+s+Exact+Test+Enrichment+Analysis

ADD REPLY
1
Entering edit mode

I am using blast2go to get GO numbers. When I am doing Fisher's exact test it was saying no result. Then I read about topGO and GOstats packages from R. So, I asked here. Now, I understood we need two gene sets for enrichment analysis. One acts as universe.

Thank you

ADD REPLY
2
Entering edit mode
6.3 years ago
ThulasiS ▴ 90

I found my answer finally We can do it in blast2go. First map the whole protein database which act as universe and retrieve annotation file from your results in blast2go and then upload your test ids list and run gene enrichment analysis. Thats all.

ADD COMMENT
1
Entering edit mode
6.3 years ago

Enrichment analysis is concerned with comparing gene sets, i.e. one asks whether a given GO term (or any other property) is over-represented in one set compared to the other. The standard way of computing this is based on the hypergeometric distribution. So you just need two annotated gene lists. How you obtained them is essentially irrelevant (although it matters for the interpretation). You can find many examples and tutorials on the subject on the web.

ADD COMMENT

Login before adding your answer.

Traffic: 2174 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6