Necorr: Necorr

Description Usage Arguments Value Author(s)

View source: R/MainFunction.R

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

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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 April 29, 2021, 6:47 a.m.