batch_pcc | R Documentation |
batch_pcc() provide a batch way to calculate the partial correlation coefficient between feature and others when controlling a third variable
batch_pcc(input, interferenceid, target, features, method = "pearson")
interferenceid |
The name of the column in the feature_data data frame representing the interference variable. |
target |
The name of the column in the pdata_group data frame representing the target variable for correlation. |
method |
The correlation method to be used. The default value is "pearson"; one of "pearson"(default), "spearman" or "kendall" |
pdata_group |
matrix;data signature matrix with multiple features |
feature_data |
A data frame containing the feature data. |
id1 |
The name of the column in the pdata_group data frame representing the ID or identifier. The default value is "ID". |
id2 |
The name of the column in the feature_data data frame representing the ID or identifier. The default value is "ID". |
Rongfang Shen
# Loading TCGA-STAD microenvironment signature data
data("sig_stad", package = "IOBR")
# Finding Pan_F_TBRs associated signature score excluding the effects of tumour purity.
res <- batch_pcc(input = sig_stad, interferenceid = "TumorPurity_estimate", target = "Pan_F_TBRs", method = "pearson", features = colnames(sig_stad)[70:ncol(sig_stad)])
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