GO slim data for GAGE GSEA analysis
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rubi ▴ 100
@rubi-6462
Last seen 3.2 years ago

Hi,

 

Is it possible to use GO slim data in a GSEA with GAGE?

 

GSEA GAGE GO • 1.2k views
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Luo Weijun ★ 1.5k
@luo-weijun-1783
Last seen 3 months ago
United States
I understand GO slim is just a concise version of GO with fine grained terms removed. GAGE definitely works with GO slim data in the right format, i.e. a named list where each element is a vector of member genes mapping to a GO term (or a pathway). Note that you don’t have to make GO slim data by youself. You can create the complete GO data with go.gsets function from the package, then use set.size=c(10, Inf) when calling gage. This way, you are creating a GO slim on the fly by removing small GO terms with less than 10 genes mapped. Of course, you may also set the upper limit like set.size=c(10, 1000) as to remove GO terms which are too general. For more details please check the gage documentation: http://bioconductor.org/packages/release/bioc/html/gage.html
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rubi ▴ 100
@rubi-6462
Last seen 3.2 years ago

Hi Lou,

I think there's another difference between applying a limited set.size, as you suggest, and GO slim. GO slim is also slim on redundancy between categories. Is there a way to test for non-redundant categories using GAGE?

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Luo Weijun ★ 1.5k
@luo-weijun-1783
Last seen 3 months ago
United States

gage package does provide a function, esset.grp(), to extract a non-redundant signcant gene set list and

related data from gage() results. For details:

library(gage)

?esset.grp

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Guangchuang Yu ★ 1.2k
@guangchuang-yu-5419
Last seen 8 months ago
China/Guangzhou/Southern Medical Univer…

another alternative solution is using GO semantic similarity to remove redundant terms, see https://guangchuangyu.github.io/2015/10/use-simplify-to-remove-redundancy-of-enriched-go-terms/

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