wTO.fast {wTO}

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))