get_diffNetworks_singleOmic {multiDEGGs} | R Documentation |
Generate differential networks for single omic analysis
Description
Generate differential networks for single omic analysis
Usage
get_diffNetworks_singleOmic(
assayData,
assayDataName,
metadata,
regression_method,
network,
percentile_vector,
padj_method,
show_progressBar,
verbose,
cores
)
Arguments
assayData |
a matrix or data.frame (or list of matrices or data.frames for multi-omic analysis) containing normalised assay data. Sample IDs must be in columns and probe IDs (genes, proteins...) in rows. For multi omic analysis, it is highly recommended to use a named list of data. If unnamed, sequential names (assayData1, assayData2, etc.) will be assigned to identify each matrix or data.frame. |
assayDataName |
name of the assayData, to identify which omic is. |
metadata |
a named vector, matrix, or data.frame containing sample
annotations or categories. If matrix or data.frame, each row should
correspond to a sample, with columns representing different sample
characteristics (e.g., treatment group, condition, time point). The colname
of the sample characteristic to be used for differential analysis must be
specified in |
regression_method |
whether to use robust linear modelling to calculate link p values. Options are 'lm' (default) or 'rlm'. The lm implementation is faster and lighter. |
network |
network of biological interactions provided by the user. The
network must be provided in the form of a table of class data.frame with only
two columns named "from" and "to".
If NULL (default) a network of 10,537 molecular interactions obtained from
KEGG, mirTARbase, miRecords and transmiR will be used.
This has been obtained via the |
percentile_vector |
a numeric vector specifying the percentiles to be
used in the percolation analysis. By default, it is defined as
|
padj_method |
a character string indicating the p values correction
method for multiple test adjustment. It can be either one of the methods
provided by the |
show_progressBar |
logical. Whether to display a progress bar during execution. Default is TRUE. |
verbose |
logical. Whether to print detailed output messages during processing. Default is TRUE |
cores |
number of cores to use for parallelisation. |
Value
a list of differential networks, one per category