Description Usage Arguments Details Value Examples
This function uses the Kolmogorov-Smirnov test as implemented by the package topGO to test for overrepresentation in Gene Ontology gene sets.
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caobj |
A "cacomp" object with principal row coordinates and standard column coordinates calculated. |
ontology |
Character string. Chooses GO sets for 'BP' (biological processes), 'CC' (cell compartment) or 'MF' (molecular function). |
organism |
Character string. Either 'hs' (homo sapiens), 'mm' (mus musculus) or the name of the organism package such as 'org.*.eg.db'. |
ngenes |
Numeric. Number of top ranked genes to test for overrepresentation. |
score_cutoff |
numeric. S-alpha score cutoff. Only genes with a score larger will be tested. |
use_coords |
Logical. Whether the x-coordinates of the row APL coordinates should be used for ranking. Only recommended when no S-alpha score (see apl_score()) can be calculated. |
return_plot |
Logical. Whether a plot of significant gene sets should be additionally returned. |
top_res |
Numeric. Number of top scoring gene sets to plot. |
For a chosen group of cells/samples, the top 'ngenes' group specific genes are used for gene overrepresentation analysis. The genes are ranked either by the precomputed APL score, or, if not available by their APL x-coordinates.
A data.frame containing the gene sets with the highest overrepresentation.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | library(Seurat)
set.seed(1234)
cnts <- GetAssayData(pbmc_small, slot = "counts")
cnts <- as.matrix(cnts)
# Run CA on example from Seurat
ca <- cacomp(pbmc_small,
princ_coords = 3,
return_input = FALSE,
assay = "RNA",
slot = "counts")
grp <- which(Idents(pbmc_small) == 2)
ca <- apl_coords(ca, group = grp)
ca <- apl_score(ca,
mat = cnts)
enr <- apl_topGO(ca,
ontology = "BP",
organism = "hs")
plot_enrichment(enr)
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