Description Usage Arguments Value Examples
LIONESS(Linear Interpolation to Obtain Network Estimates for Single Samples) is a method to estimate sample-specific regulatory networks. [(LIONESS arxiv paper)]).
1 2 | runLioness(e = expression, m = motif, ppi = ppi,
rm_missing = FALSE)
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e |
Character String indicatining the file path of expression values file, as each gene (row) by samples (columns) required |
m |
Character String indicatining the file path of pair file of motif edges, when not provided, analysis continues with Pearson correlation matrix. optional |
ppi |
Character String indicatining the pair file path of Protein-Protein interaction dataset. optional |
rm_missing |
Boolean indicatining whether to remove missing values. If TRUE, removes missing values. if FALSE, keep missing values. THe default value is FALSE. optional |
A data frame with columns representing each sample, rows representing the regulator-target pair in PANDA network generated by runPanda
.
Each cell filled with the related score, representing the estimated contribution of a sample to the aggregate network.
1 2 3 4 5 6 7 | # refer to the input datasets files of control in inst/extdat as example
control_expression_file_path <- system.file("extdata", "expr10.txt", package = "netZoo", mustWork = TRUE)
motif_file_path <- system.file("extdata", "chip.txt", package = "netZoo", mustWork = TRUE)
ppi_file_path <- system.file("extdata", "ppi.txt", package = "netZoo", mustWork = TRUE)
# Run PANDA algorithm
control_lioness_result <- runLioness(e = control_expression_file_path, m = motif_file_path, ppi = ppi_file_path, rm_missing = TRUE )
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