Connect gene names to GO terms/function for loading in DESeq2
1
0
Entering edit mode
5.7 years ago
Moneeb Bajwa ▴ 10

Hi,

I would like to connect the gene names to GO terms and function before loading them into DESeq2. The counts are from single-end mouse reads mapped to the genome and annotation files from GENCODE.

The counts files I have look like this right now:

   gene_id               counts     gene_name
1 ENSMUSG00000064842.1      0       Gm26206
2 ENSMUSG00000051951.5      4          Xkr4
3 ENSMUSG00000102851.1      0 RP23-317L18.1
4 ENSMUSG00000103377.1      0 RP23-317L18.4
5 ENSMUSG00000104017.1      0 RP23-317L18.3
6 ENSMUSG00000103025.1      0  RP23-115I1.6

I intend on making a graph similar to Figure D in this link (taken from the paper that performed this study already): http://cancerres.aacrjournals.org/content/canres/78/5/1334/F5.large.jpg. This is their full paper: http://cancerres.aacrjournals.org/content/78/5/1334

Not sure what to do. I appreciate the help.

DESeq2 rna-seq GO terms Annotation R • 1.4k views
ADD COMMENT
1
Entering edit mode
5.7 years ago
Prakash ★ 2.2k

In Figure D , what they have shown is enriched GO terms for 363 AKT differentially expressed genes. GO terms and DESeq2 analysis are two different things. you can find enriched GO terms for whole set of gene but that would be very less meaningful. I would rather first go for differential expression analysis using DESeq2 and then do GO term enrichment analysis.

Thanks

ADD COMMENT
0
Entering edit mode

Thank you. But how would I get the GO annotations for that? I tried a couple websites like https://go.princeton.edu/cgi-bin/GOTermFinder but I don't understand why it doesn't give me any results? I just put like RP23-115I1.6 and select mouse genome it should return something right? It didn't work.

ADD REPLY
1
Entering edit mode

The link you tried will only provide enriched GO terms for you set of genes, basically it compares your set of genes against respective databases and calculates enrichment and significance. providing only one gene will not return anything. If you really interested in only GO annotation, then you should try biomaRt R package or just download GO annotation file extract GO ID

ADD REPLY

Login before adding your answer.

Traffic: 1973 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