View source: R/create.counts.table.R
create.counts.table | R Documentation |
Summary function to collapse the counts of selected (e.g. correlated) features per cancer type into counts table
create.counts.table(corr.summary = NULL)
corr.summary |
A list object containing subtype specific selected (e.g. correlated) features. This is the list object returned by |
A matrix of cancer type specific counts
Syed Haider
estimate.expression.cna.correlation
# load test data
x <- get.test.data(data.types = c("mRNA.T", "CNA"));
# temporary output directory
tmp.output.dir <- tempdir();
# go through each cancer type iteratively and perform mRNA-CNA correlation analysis
correlated.features <- list();
for (cancer.type in names(x$mRNA.T)) {
# estimate mRNA and CNA correlation for each cancer/disease type
correlated.features[[cancer.type]] <- estimate.expression.cna.correlation(
exp.data = x$mRNA.T[[cancer.type]],
cna.data.log2 = x$CNA.log2[[cancer.type]],
corr.threshold = 0.3,
corr.direction = "two.sided",
subtypes.metadata = list(
"subtype.samples.list" = list("All" = colnames(x$mRNA.T[[cancer.type]]))
),
feature.ids = rownames(x$mRNA.T[[cancer.type]]),
cancer.type = cancer.type,
data.dir = paste(tmp.output.dir, "/data/", cancer.type, sep = ""),
graphs.dir = paste(tmp.output.dir, "/graphs/", cancer.type, sep = "")
);
}
# create counts table across cancer types
counts.table <- create.counts.table(corr.summary = correlated.features);
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