Title: | An Algorithm for Gene Co-Expression Analysis |
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Description: | Implementation based on Zhang, Jie & Huang, Kun (2014) <doi:10.4137/CIN.S14021> Normalized ImQCM: An Algorithm for Detecting Weak Quasi-Cliques in Weighted Graph with Applications in Gene Co-Expression Module Discovery in Cancers. Cancer informatics, 13, CIN-S14021. |
Authors: | Zhi Huang [aut, cre], Jie Zhang [aut, ctb], Kun Huang [aut, ctb], Zhi Han [aut, ctb] |
Maintainer: | Zhi Huang <[email protected]> |
License: | MIT + file LICENSE |
Version: | 0.2.4 |
Built: | 2025-02-25 04:32:15 UTC |
Source: | https://github.com/huangzhii/lmqcm |
Author: Zhi Huang
fastFilter( RNA, lowest_percentile_mean = 0.2, lowest_percentile_variance = 0.2, var.func = "var" )
fastFilter( RNA, lowest_percentile_mean = 0.2, lowest_percentile_variance = 0.2, var.func = "var" )
RNA |
an expression matrix (rows: genes; columns: samples) |
lowest_percentile_mean |
a float value range 0-1 |
lowest_percentile_variance |
a float value range 0-1 |
var.func |
specify variance function |
An filtered expression matrix
Author: Zhi Huang
lmQCM( data_in, gamma = 0.55, t = 1, lambda = 1, beta = 0.4, minClusterSize = 10, CCmethod = "pearson", positiveCorrelation = F, normalization = F )
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)$exprs data = fastFilter(data, 0.2, 0.2) lmQCM(data)
library(lmQCM) library(Biobase) data(sample.ExpressionSet) data = assayData(sample.ExpressionSet)$exprs data = fastFilter(data, 0.2, 0.2) lmQCM(data)
Author: Zhi Huang
localMaximumQCM(cMatrix, gamma = 0.55, t = 1, lambda = 1)
localMaximumQCM(cMatrix, gamma = 0.55, t = 1, lambda = 1)
cMatrix |
a correlation matirx |
gamma |
gamma value (default = 0.55) |
t |
t value (default = 1) |
lambda |
lambda value (default = 1) |
An unmerged clusters group 'C'
Author: Zhi Huang
merging_lmQCM(C, beta = 0.4, minClusterSize = 10)
merging_lmQCM(C, beta = 0.4, minClusterSize = 10)
C |
Resulting clusters |
beta |
beta value (default = 0.4) |
minClusterSize |
minimum length of cluster to retain (default = 10) |
mergedCluster - An merged clusters group