Comments (3)
Note about using a higher numbers of permutations.
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Tried running the code as is in the lesson but I get the no terms enriched. Setting nPerm=2000 or even 5000 is not noticeable in terms of running time, and it results in a set of terms that are now enriched.
How did terms go from being not significant to significant? The nPerm parameter specifies how many times this randomization is done and more randomizations are performed, the more precise the FDR Q value estimation will be. So at 1000 a good chunk of terms all get the same estimate of 0.07. With more permutations you will find that the individual terms will obtain more accurate values rather than binned shared value.
Problem is, now the term that we use in the lesson for the GSEplot is not showing up. My results have changed.
Solution, remove the GSEgo section and just add a note. Go terms are better assessed with ORA
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updated lesson
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Related Issues (19)
- paring down the dispersion lesson HOT 1
- a note for the warning in dotplot HOT 3
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- Add note about knockout genes continuing to be expressed HOT 2
- for cluster profiler new msigdbr package HOT 2
- Create project with data and folders HOT 1
- apeglm stat removed HOT 2
- Adding gene names to KEGG output HOT 2
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- clusterProfiler for gene lists split by expression change HOT 1
- Creating annotation file tx2gene for NCBI human transcriptome HOT 1
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