lmQCM | R Documentation |
Author: Zhi Huang
lmQCM( data_in, gamma = 0.55, t = 1, lambda = 1, beta = 0.4, minClusterSize = 10, CCmethod = "pearson", positiveCorrelation = F, normalization = F )
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. |
QCMObject - An S4 Class with lmQCM results
library(lmQCM) library(Biobase) data(sample.ExpressionSet) data = assayData(sample.ExpressionSet)$exprs data = fastFilter(data, 0.2, 0.2) lmQCM(data)
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