Question: DESeq2 followed by GSEA
4
gravatar for langya
3.1 years ago by
langya90
langya90 wrote:

I recently analyzed my RNA-Seq data followed by STAR-HTSeqCount-DESeq2 method and want to run these on GSEA to find correlation with certain pathways. But for the input, should I prerank the genes based on Log2FC or log(p-value) * sign_of_FC. If use the later case, how should I choose the parameter of GSEA? And in all these ranking process, should i use 0.01 as cutoff for p-adj (FDR) to cut off other genes.

gsea rna-seq next-gen R gene • 3.6k views
ADD COMMENTlink modified 3.1 years ago by Ram160 • written 3.1 years ago by langya90
1
gravatar for Ram
3.1 years ago by
Ram160
Germany
Ram160 wrote:

I think there are two ways of generating the GSEA preranked list: 1) by log2FC; 2) by p value.

You might take a look at this previous thread:

Gene Set Enrichment Analysis after DESeq2

ADD COMMENTlink written 3.1 years ago by Ram160

THANKS! But I didnt understand about the p-adj part. Shouldnt i use any cutoff for p-adj to filter out some genes?

ADD REPLYlink written 3.0 years ago by langya90

Below mentioned is the description from DESeq2 Vignette for p-values in case for p-adj :

 By default, independent filtering is performed to select a set of
 genes for multiple test correction which will optimize the number
 of adjusted p-values less than a given critical value ‘alpha’ (by
 default 0.1). The adjusted p-values for the genes which do not
 pass the filter threshold are set to ‘NA’. By default, the mean of
 normalized counts is used to perform this filtering, though other
 statistics can be provided. Several arguments from the
 ‘filtered_p’ function of genefilter are provided here to control
 or turn off the independent filtering behavior.

 By default, ‘results’ assigns a p-value of ‘NA’ to genes
 containing count outliers, as identified using Cook's distance.
 See the ‘cooksCutoff’ argument for control of this behavior.
 Cook's distances for each sample are accessible as a matrix
 "cooks" stored in the ‘assays()’ list. This measure is useful for
 identifying rows where the observed counts might not fit to a
 Negative Binomial distribution.
ADD REPLYlink written 3.0 years ago by Ram160

If use basemean to filter out genes, do you know what cutoff i should use to filter out? Also, my baseMean between two biologcial replicates are very high but not the log2foldchange or p-val. So should I use baseMean for GSEA analysis? Thanks!

ADD REPLYlink written 3.0 years ago by langya90
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 1500 users visited in the last hour
_