directPA | R Documentation |
The main function of direction Analysis. This function takes in a matrix of test statistics with two (2-dimensional space) or three (3-dimensional space) columns, the direction of interests, and the annotation list such as pathway annotation, and test for enrichment of pathways on the specified direction.
directPA(Tc, direction, annotation, minSize=5, gene.method="OSP",
path.method="Stouffer", visualize=TRUE, ...)
Tc |
a numeric matrix. Rows are genes and columns are treatments vs control statistics. |
direction |
the direction to be tested for enrichment. Either specified as a degree for two-dimensional analysis or as contrast (in a triplet) for three-dimensional analysis. |
annotation |
a list with names correspond to pathways and elements correspond to genes belong to each pathway, respectively. |
minSize |
the size of annotation groups to be considered for calculating enrichment. Groups that are smaller than the minSize will be removed from the analysis. |
gene.method |
the method to be used for integrating statistics across treatments for each gene. Available methods are Stouffer, OSP, Fisher, and maxP. Default method is OSP. |
path.method |
the method to be used for integrating statistics of all genes that belongs to a pathway. Available methods are Stouffer, OSP, Fisher, and maxP. Default method is Stouffer. |
visualize |
whether to visualize the plot. |
... |
other visualization parameters to pass on. |
a list that contains directional p-values for each gene and directional enrichment for each pathway.
# load the proteomics dataset
data(PM)
# load pathway annotations
data(Pathways)
# display reactome pathways. Could be replaced by any other pathway databases
Pathways.reactome[1:5]
# direction pathway analysis in 3-dimensional space. Implemnted as rotating by contrast
# (1) test combined effect of all 3 treatments (stimulation and inhibitions) vs control (basal)
# on the original direction.
dPA <- directPA(Tc=PM, direction=c(1,1,1), annotation=Pathways.reactome)
dPA$gst[order(unlist(dPA$gst[,1])),][1:20,]
# rank substrates on the direciton of interest
sort(dPA$gene.pvalues)[1:20]
# (2) test combined effect of all 3 treatments vs controls on direction c(1,-1, 0)
# this rotates Ins by 0 degree, Wmn by 90 degree, and MK by 45 degree.
dPA <- directPA(Tc=PM, direction=c(1,-1,0), annotation=Pathways.reactome)
dPA$gst[order(unlist(dPA$gst[,1])),][1:20,]
# (3) test combined effect of all 3 perturbations vs controls on direction c(1,-1, 1)
# this rotates Ins by 0 degree, Wmn by 90 degree, and MK by 0 degree.
dPA <- directPA(Tc=PM, direction=c(1,-1,1), annotation=Pathways.reactome)
dPA$gst[order(unlist(dPA$gst[,1])),][1:20,]
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