c_score: Computing the mean and variance combined signal scores

In NEpiC: Network Assisted Algorithm for Epigenetic Studies Using Mean and Variance Combined Signals

Description

A function computing gene-level scores combining both signals in mean and variance differences.

Usage

c_score(mean_sig, var_sig, lambda = "default")

Arguments

mean_sig	A dataframe describing mean signals for every CpG sites. Three columns are needed in this dataset, which are 'cpg', 'gene' and 'mean_p'. 'cpg' column has names of CpG sites. 'gene' column has has gene annotations for CpG sites. 'mean_p' column has p values of mean differences for CpG sites.
var_sig	A dataframe describing variance signals for every CpG sites. Three columns are needed in this dataset, which are 'cpg', 'gene' and 'var_p'. 'cpg' column has names of CpG sites. 'gene' column has has gene annotations for CpG sites. 'var_p' column has p values of variance differences for CpG sites.
lambda	A parameter to balance mean and variance scores. NEpiC computes it as default if it is not otherwise specified by user. If lambda = 1, NEpiC will search dense modules using only mean signals. If lambda = 0, NEpiC will search dense modules using only variance signals. Users can also specify any float between 0 and 1 for lambda if they have any additional prior biology information.

Value

c_score returns a dataframe describing the combined gene-level scores, which can be used directly in c_dms.

References

NEpiC: a Network-assisted algorithm for Epigenetic studies using mean and variance Combined signals. Peifeng Ruan, Jing Shen, Regina M. Santella, Shuigeng Zhou, Shuang Wang.(2015)

Examples

#c_score(mean_sig, var_sig, lambda = "default")

NEpiC documentation built on May 1, 2019, 10:29 p.m.