View source: R/corrOrthologTE.R
corrOrthologTE | R Documentation |
To estimate correlation comparing orthologs and TEs one-by-one from inputs. You can specify the correlation and adjusted p-value methods (see details in parameters). If you want to save your outputs instead of just returning them, please specify the fileDir and fileName with the extension .csv. The default fileName is TEKRABber_geneTECorrReusult.csv.
corrOrthologTE(geneInput, teInput, corrMethod = "pearson",
padjMethod = "fdr", numCore=1, fileDir=NULL,
fileName="TEKRABber_geneTECorrResult.csv")
geneInput |
gene count input for correlation from using DECorrInputs() |
teInput |
te count input for correlation from using DECorrInputs() |
corrMethod |
correlation method, including pearson, kendall, spearman. Default is pearson. |
padjMethod |
method to return adjusted p-value, and default is fdr. See ?p.adjust |
numCore |
number of cores to run parallel. Default is 1. You can use detectCores() to get how many cores you can use. |
fileDir |
the name of directory for saving output files. Default is NULL. |
fileName |
the name for saving output files. Default is "TEKRABber_geneTECorrResult.csv" |
a dataframe includes correlation coefficient, pvalue, padj
data(ctInputDE)
geneInputDE <- ctInputDE$gene
teInputDE <- ctInputDE$te
metaExp <- data.frame(experiment = c(rep("control", 5), rep("treatment", 5)))
rownames(metaExp) <- colnames(geneInputDE)
metaExp$experiment <- factor(
metaExp$experiment,
levels = c("control", "treatment")
)
resultDE <- DEgeneTE(
geneTable = geneInputDE,
teTable = teInputDE,
metadata = metaExp,
expDesign = FALSE
)
controlCorr <- corrOrthologTE(
geneInput = resultDE$geneCorrInputRef[c(1:10),],
teInput = resultDE$teCorrInputRef[c(1:10),],
numCore = 1,
corrMethod = "pearson",
padjMethod = "fdr"
)
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