Necorr: Necorr

View source: R/MainFunction.R

NecorrR Documentation

Necorr

Description

NECorr helps discover candidate genes that could be important for specific conditions. The principal inputs are the expression data and the network file. The expression data should start with 3 header columns. The first column describes the conditions. Each condition will be treated separately for the co-expression analysis The output of the program will be generated in a result folder generated in the working path Create the output directory if not existing; generate "./results" dir and "./results/tmp" C.Liseron-Monfils - Ware lab Sept2013 - CSHL partly based on rsgcc package for the GCC, PCC,KCC and SPP Ma et al, 2012, plant Physiology

Usage

Necorr(
  networkFile = "",
  expression = "",
  description.file = "",
  condition = "",
  metadata = "",
  name = "",
  Filelist = "",
  method = "GCC",
  permutation = 1000,
  sigcorr = 0.01,
  fadjacency = "only",
  type = "gene",
  NSockets = 2
)

Arguments

networkFile

Molecular network file with source in the first column, targets in the second column

expression

Expression file in log2 (ratio expression) with row: gene, first column: type of sample,second column: sample names

description.file

genome description

condition

Condition from expression to study the network co-expression correlation

metadata

dataframe with the metadata

name

the name of the

Filelist

condition list see if still necessary with metadata

method

used for co-expression correlation: GCC, MINE, PCC, SCC or KCC

permutation

permutation number used for all significance calculation #param lmiR List of miRNAs

sigcorr

significance of the correlation

fadjacency

correlation with all combination (all) or network combination only (only)

type

Omics comparative expression type: protein or gene

NSockets

number of sockets

Value

res

Author(s)

Christophe Liseron-Monfils, Andrew Olson


warelab/NECorr documentation built on June 25, 2024, 7:25 a.m.