lmQCM (version 0.2.2)

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",
  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".

normalization

Determine if normalization is needed on massive correlation coefficient matrix.

Value

QCMObject - An S4 Class with lmQCM results

Examples

Run this code
# NOT RUN {
library(lmQCM)
library(Biobase)
data(sample.ExpressionSet)
data = assayData(sample.ExpressionSet)$exprs
data = fastFilter(data, 0.2, 0.2)
lmQCM(data)

# }

Run the code above in your browser using DataCamp Workspace