lmQCM {lmQCM}

lmQCM: Main Routine for Gene Co-expression Analysis

Description

Author: Zhi Huang

Usage

lmQCM(
  data_in,
  gamma = 0.55,
  t = 1,
  lambda = 1,
  beta = 0.4,
  minClusterSize = 10,
  CCmethod = "pearson",
  positiveCorrelation = F,
  normalization = F
)

Arguments

data_in

real-valued expression matrix with rownames indicating gene ID or gene symbol

gamma

gamma value (default = 0.55)

t

t value (default = 1)

lambda

lambda value (default = 1)

beta

beta value (default = 0.4)

minClusterSize

minimum length of cluster to retain (default = 10)

CCmethod

Methods for correlation coefficient calculation (default = "pearson"). Users can also pick "spearman".

positiveCorrelation

This determines if correlation matrix should convert to positive (with abs function) or not.

normalization

Determine if normalization is needed on massive correlation coefficient matrix.

Value

QCMObject - An S4 Class with lmQCM results

Examples

library(lmQCM)
library(Biobase)
data(sample.ExpressionSet)
data = assayData(sample.ExpressionSet)$exprs
data = fastFilter(data, 0.2, 0.2)
lmQCM(data)