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Enrichment analysis on TCGA data

Hi,

I have a list of differentially expressed genes between tumor and normal samples determined from TCGA data (BRCA). I am trying to cluster the genes into related groups and determine gene annotations for each cluster. The clustering is no problem, but annotating the clusters is proving to be difficult. I have tried using the TCGA_Biolinks function TCGAanalyze_EAcomplete, however I do not know how to make sense out of the output of this function. I have followed the tcgabiolinks vignette, and made the EABarplot (I could only get this to work for the dataset provided, not for a different dataset downloaded from the gdc), however I dont know how to get access to the genes that make up the different bars in the plot. I would like to find, for instance, a set of genes that are related to T-cell activity.

Thank you, David

rna-seq tcgabiolinks

how to download tumor and normal samples from TCGA database?

2 answers

Method 1:

1) Use GeneSCF to extract complete Gene Ontology as simple text (tab separated) format.

./prepare_database -db=GO_all -org=goa_human

2) Extract the genes related to you keyword 'T cell'

grep "T cell" geneSCF-master-source-v1.1-p2/class/lib/db/goa_human/GO_all_sym.txt | cut -f2 | sed s'/.$//' | sed 's/,/\n/g' | awk '!x[$0]++'

3) Overlap those genes with your list of genes

Method 2:

If you are confident that the genes you have, are related to 'T cell', try simple gene enrichment analysis with GeneSCF and check if the 'T cell activity' terms pops up.

Hi EagleEye,

Thank you very much for your response. That seems to be what I am trying to do, however I would like to keep my analysis in R. Is there a tool that works in R that does a similar task?

Thank you, David

I do not know if this task can be easily done with R. Alternatively you can import the table/TEXT file obtained with GeneSCF ('geneSCF-master-source-v1.1-p2/class/lib/db/goa_human/GO_all_sym.txt') into R and match your gene list.

Hi EagleEye,

Thank you very much for your response. That seems to be what I am trying to do, however I would like to keep my analysis in R. Is there a tool that works in R that does a similar task?

Thank you, David

Please move this as a comment to EagleEye's answer. You should reply it to that thread and not create an answer on your own if its not an answer. This makes the post true to its term. I hope Moderator take note and do the needful. P.S: My comment can be deleted after the answer of the OP is moved as a comment. Thanks

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