Hello there,
I did standard GSEA for my microarray expression data. As I found out GSEA tools provide GSEA plot just for top 20 of enriched pathways. How can I provide plot for other pathways which are also significantly enriched (adj-pval < 0.05) in my dataset based on GSEA?
I am trying fgsea package in r. Could anyone please bring an example here that shows, how the input should look like for plotEnrichment()? What's wrong with my input?
I want to plot for TGFb gene set and this is my script : plotEnrichment(tgfb_gene, gene_list, gseaParam = 1, ticksSize = 0.2)
so for the first argument, examplePathway I used this list:
> tgfb_gene
$HALLMARK_TGF_BETA_SIGNALING
[1] "TGFBR1" "SMAD7" "TGFB1" "SMURF2" "SMURF1" "BMPR2" "SKIL"
[8] "SKI" "ACVR1" "PMEPA1" "NCOR2" "SERPINE1" "JUNB" "SMAD1"
[15] "SMAD6" "PPP1R15A" "TGIF1" "FURIN" "SMAD3" "FKBP1A" "MAP3K7"
[22] "BMPR1A" "CTNNB1" "HIPK2" "KLF10" "BMP2" "ENG" "APC"
[29] "PPM1A" "XIAP" "CDH1" "ID1" "LEFTY2" "CDKN1C" "TRIM33"
[36] "RAB31" "TJP1" "SLC20A1" "CDK9" "ID3" "NOG" "ARID4B"
[43] "IFNGR2" "ID2" "PPP1CA" "SPTBN1" "WWTR1" "BCAR3" "THBS1"
[50] "FNTA" "HDAC1" "UBE2D3" "LTBP2" "RHOA"
and for the second argument, exampleRanks, I used a vector of the logFC (output of differential gene expression analysis), the names of vector is the name of genes. But I got this error and warnings:
Error: Aesthetics must be either length 1 or the same as the data (1): x, xend
In addition: Warning messages:
1: In max(tops) : no non-missing arguments to max; returning -Inf
2: In min(bottoms) : no non-missing arguments to min; returning Inf
3: In max(tops) : no non-missing arguments to max; returning -Inf
4: In min(bottoms) : no non-missing arguments to min; returning Inf
5: In max(tops) : no non-missing arguments to max; returning -Inf
6: In min(bottoms) : no non-missing arguments to min; returning Inf
Is there any other ways to provide or re-plot GSEA results?
I really appreciate any help!!
Many thanks @gabrit. I did it. I am trying to add title for my plot. Do you know how I can do it?
which plot of the many listed in the tutorial are you referring to?