createCytoGraph | R Documentation |
Creates graphs of protein-gene interactions based on enrichment analyses by this pipeline
createCytoGraph(enrichment, ents, rels, DEGs, p.thresh=0.05,
fc.thresh = log(1.5), numProt=5, ids=NA,
numTargets=10)
enrichment |
The enrichment tables from the analysis pipeline. Can be a list of lists (multiple methods and conditions) or a list (multiple conditions, one method), or a single data frame |
ents |
The ents table used in the enrichment, must be a single data frame |
rels |
The rels table used in the enrichment, must be a single data frame |
DEGs |
The differentially expressed gene tables, can be a single data frame or list of data frames matching that which the pipeline was run on. |
p.thresh |
The p value threshold used in determining the significant differentailly expressed genes for enrichment analysis |
fc.thresh |
The fold count threshold used in determining the significant differentially expressed genes for enrichment analysis |
numProt |
The number of protiens, ranked by p.value from enrichment, to include |
ids |
Row indices of the regulators you wish to be included in the plot |
numTargets |
The number of targets of each top regulator to show. Please note that the number of targets plotted may be smaller than you expect, due to overlap. |
Opens a browser window with the graph, green = proteins, purple = mRNA
ChIP1ap <- filterChIPAtlas(1, NA, "auto", NA, "prostate", NA, NA, FALSE)
files <- list.files("./", ".txt")
degs <- lapply(files, function(x) {
read.table(x, header=T, sep="\t") } )
names(degs) <- files
methods <- c("Ternary", "Quaternary", "Enrichment", "Fisher")
enrichment <- runInferenceModels(NULL, NULL, DEGs=degs,
method = methods,
ents=ChIP1ap$filteredChIP.ents,
rels=ChIP1ap$filteredChIP.rels,
useFile=F, useMart=TRUE, useBHLH=TRUE,
martFN="../CIE/data/mart_human_TFs.csv",
BHLHFN="../CIE/data/BHLH_TFs.txt")
createCytoGraph(enrichment, ChIP1ap$filteredChIP.ents,
ChIP1ap$filteredChIP.rels, degs)
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