Question: RNa seq data: GO annotation
1
gravatar for hnp21
3.5 years ago by
hnp2140
United States
hnp2140 wrote:

Hello Biotsrars!

I have a question for you about GO annotation of RNA seq data: I have differentially expressed genes (used Edge R to analyze RNA seq data) and I need know GO terms of those genes. I have GO terms for most of the transcripts and I got those GO terms (with IDs) directly from the reference genome I used for the analysis. I want to know whether those GO terms (got directly from the reference) are enough OR is it necessary to do a GO analysis on RNA seq data using those programs available such as BLAST2GO, Go seq ect.?

I greatly appreciate your inputs!


EDIT:

I'm sorry for not stating my question clearly. This is what I wanted to ask:

After analyzing RNA seq data, we assigned GO terms for deferentially expressed genes based on GO terms given by the reference assembly. We didn't do a separate GO analysis for RNA seq data. So what would you think about it? Is getting GO terms directly from the reference assembly is enough? OR do we have to do a separate GO analysis for the data?

sequencing rna-seq gene • 1.8k views
ADD COMMENTlink modified 6 months ago by RamRS25k • written 3.5 years ago by hnp2140
1

You have to do a GO analysis on the DEGs. However you got an GO lists annotated to the genes by the reference assembly, you can not believe whether the GO lists are significantly enriched to the DEGs or not.

You can easily find the RNA-seq DEG analysis using GO enrichment analysis. ex) http://europepmc.org/abstract/med/26952511

DAVID tool is the most common tool for GO analysis.

ADD REPLYlink written 3.5 years ago by sosal10
1
gravatar for jeremy.cox.2
3.5 years ago by
jeremy.cox.290
United States
jeremy.cox.290 wrote:

Have you tried GOlorize, BiNGO, and ClueGO in Cytoscape? Many of these tools support importing gene symbols.

ADD COMMENTlink written 3.5 years ago by jeremy.cox.290
1
gravatar for EagleEye
3.5 years ago by
EagleEye6.5k
Sweden
EagleEye6.5k wrote:

Gene Set Clustering based on Functional annotation (GeneSCF)

http://genescf.kandurilab.org

ADD COMMENTlink written 3.5 years ago by EagleEye6.5k
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