Fast Gene Set Enrichment Analysis (FGSEA) of transcriptomics and proteomics differential analysis results using Gene Ontology terms from the Molecular Signatures Database (MSigDB v7.5.1).
TRNSCRPT_FGSEA # transcriptomics
PROT_FGSEA # proteomicsA named list of 3 data.frame objects:
All trained timepoints compared to their sex-matched sedentary control group. Example: F_1W - F_SED. Total of 8 contrasts.
Sedentary males compared to sedentary females. Only 1 contrast.
Comparisons of the male and female training responses. Example: (M_8W - M_SED) - (F_8W - F_SED). Total of 4 contrasts.
Each data.frame contains the following 12 variables:
character; Gene Ontology pathway identifier.
character; GO:BF (Biological Processes), GO:MF (Molecular Functions), or GO:CC (Cellular Components). See http://geneontology.org/docs/ontology-documentation/
character; Gene Ontology set description. See
update_GO_names for details.
numeric; enrichment p-value.
numeric; BH-adjusted p-value. P-values are adjusted across all contrasts within each ontology (GO:BP, GO:CC, GO:MF).
numeric; the expected error for the standard deviation of the p-value logarithm.
numeric; gene set enrichment score.
numeric; normalized enrichment score. Accounts for differences in gene set size. Calculated as the quotient of the ES to the absolute mean of the permutation enrichment scores that have the same sign as the ES. See https://doi.org/10.1101/060012 for details. Values in [-1, 1] are not interesting.
integer; number of genes in each pathway after it has been filtered to those that were present in the differential analysis results.
character; the comparison being made.
list; the Entrez gene IDs that drive the enrichment. If the set has a negative ES, the genes are arranged from most to least negative; otherwise, they are arranged from most to least positive. See http://software.broadinstitute.org/gsea/doc/GSEAUserGuideTEXT.htm#_Running_a_Leading.
list; the leadingEdge after mapping
Entrez genes to more human-readable gene symbols. Any genes that could
not be mapped were discarded, so lengths(leadingEdge_genes) may
not match lengths(leadingEdge).
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