wTO.fast: wTO.fast

In wTO: Computing Weighted Topological Overlaps (wTO) & Consensus wTO Network

wTO.fast

Description

Compute the wTO and also the bootstraps. Proposed at arXiv:1711.04702. This is a quicker version of the wTO.Complete. It doesn't contain diagnose plots nor a parallel version.

Usage

wTO.fast(
  Data,
  Overlap = row.names(Data),
  method = "p",
  sign = "sign",
  delta = 0.2,
  n = 10,
  method_resampling = "Bootstrap",
  lag = NULL,
  ID = NULL
)

Arguments

Data	data.frame containing the count / expression data for the correlation.
Overlap	Set of nodes of interest, where the Overlapping weights will be computed.
method	Type of the correlation that should be used. "s" / "spearman" will compute the rank spearman correlation, "p" / "pearson" will compute the linear correlation. If no value is given, the default is to use "p".
sign	Should the wTO be signed?
delta	expected difference between the real wTO and the bootstraped.
n	Number of resamplings, used to compute the empirical distribuitions of the links. Default is set to 100.
method_resampling	method of the resampling. Bootstrap or BlockBootstrap.If the second is used, please give the lag (time dependency among the data).
lag	Time dependency for the blocked bootstrap (for time series).
ID	ID of the samples for the blocked bootstrap (for repeated measures).

Author(s)

Deisy Morselli Gysi <deisy at bioinf.uni-leipzig.de>

Examples

# wTO.fast(Data = Microarray_Expression1,
# Overlap = ExampleGRF$x, 
# method = "p")

# For a time series with lag = 4
# wTO.fast(Data = Microarray_Expression1,
# Overlap = ExampleGRF$x, 
# method = "p", 
# method_resampling = 'BlockBootstrap', 
# lag = 4)

# For a study where the individuals were measured multiple times.
# wTO.fast(Data = Microarray_Expression1,
# Overlap = ExampleGRF$x, 
# method = "p", 
# method_resampling = 'BlockBootstrap', 
# ID = rep(1:9, each= 2))

wTO documentation built on March 31, 2023, 6:31 p.m.