| 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