Type: | Package |
Title: | An Algorithm for Gene Co-Expression Analysis |
Version: | 0.2.4 |
Date: | 2022-10-09 |
Author: | Zhi Huang [aut, cre], Jie Zhang [aut, ctb], Kun Huang [aut, ctb], Zhi Han [aut, ctb] |
Maintainer: | Zhi Huang <hz9423@gmail.com> |
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. |
License: | MIT + file LICENSE |
Encoding: | UTF-8 |
Depends: | genefilter, Biobase, progress, stats, methods |
Suggests: | devtools, roxygen2 |
RoxygenNote: | 7.2.1 |
URL: | https://github.com/huangzhii/lmQCM/ |
BugReports: | https://github.com/huangzhii/lmQCM/issues/ |
NeedsCompilation: | no |
Packaged: | 2022-10-10 05:23:25 UTC; zhihuang |
Repository: | CRAN |
Date/Publication: | 2022-10-10 07:30:02 UTC |
fastFilter: Subroutine for filtering expression matrix
Description
Author: Zhi Huang
Usage
fastFilter(
RNA,
lowest_percentile_mean = 0.2,
lowest_percentile_variance = 0.2,
var.func = "var"
)
Arguments
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 |
Value
An filtered expression matrix
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)
localMaximumQCM: Subroutine for Creating Gene Clusters
Description
Author: Zhi Huang
Usage
localMaximumQCM(cMatrix, gamma = 0.55, t = 1, lambda = 1)
Arguments
cMatrix |
a correlation matirx |
gamma |
gamma value (default = 0.55) |
t |
t value (default = 1) |
lambda |
lambda value (default = 1) |
Value
An unmerged clusters group 'C'
merging_lmQCM: Subroutine for Merging Gene Clusters
Description
Author: Zhi Huang
Usage
merging_lmQCM(C, beta = 0.4, minClusterSize = 10)
Arguments
C |
Resulting clusters |
beta |
beta value (default = 0.4) |
minClusterSize |
minimum length of cluster to retain (default = 10) |
Value
mergedCluster - An merged clusters group