optimCutOff: optimum cutoff for a correlation or spectral similarity...
In WMBEdmands/compMS2Miner: an automatable metabolite identification, visualization and data-sharing R package for high-resolution LC-MS datasets
Description
Usage
Arguments
Value
References
Description
optimum cutoff for a correlation or spectral similarity matrix
Usage
1
2
optimCutOff(x = NULL, cutOffSeq = seq(0.01, 1, 0.01), diffConsecVals = 1.5
* 10^-3, maxCutOff = 0.95)
Arguments
x
matrix of correlation coefficients or spectral similarity values
column and row names must match
cutOffSeq
numeric a vector of cut-off values to test. (default=seq(0.01, 1, 0.01) a numeric vector of length 100)
diffConsecVals
numeric the scaled difference between consecutive values
to identify the plateau in the network density (default=1.5*10^-3 or 0.0015).
Value
a list containing two named elements "estCutOff" a numeric estimated optimal cut-off value and "testData" a matrix
of the test results at each cut-off value. The function also plots the result.
References
Koh Aoki, Yoshiyuki Ogata, and Daisuke Shibata
Approaches for Extracting Practical Information from Gene Co-expression Networks in Plant Biology
Plant Cell Physiol (2007) 48 (3): 381-390 first published online January 23, 2007 doi:10.1093/pcp/pcm013
WMBEdmands/compMS2Miner documentation built on May 9, 2019, 10:04 p.m.
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Description Usage Arguments Value References
Description
optimum cutoff for a correlation or spectral similarity matrix
Usage
1 2 | optimCutOff(x = NULL, cutOffSeq = seq(0.01, 1, 0.01), diffConsecVals = 1.5
* 10^-3, maxCutOff = 0.95)
|
Arguments
x |
matrix of correlation coefficients or spectral similarity values column and row names must match |
cutOffSeq |
numeric a vector of cut-off values to test. (default=seq(0.01, 1, 0.01) a numeric vector of length 100) |
diffConsecVals |
numeric the scaled difference between consecutive values to identify the plateau in the network density (default=1.5*10^-3 or 0.0015). |
Value
a list containing two named elements "estCutOff" a numeric estimated optimal cut-off value and "testData" a matrix of the test results at each cut-off value. The function also plots the result.
References
Koh Aoki, Yoshiyuki Ogata, and Daisuke Shibata Approaches for Extracting Practical Information from Gene Co-expression Networks in Plant Biology Plant Cell Physiol (2007) 48 (3): 381-390 first published online January 23, 2007 doi:10.1093/pcp/pcm013
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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