cn_clr: make a CLR-like matrix for assessment purposes
In pcahan1/CellNet: Assess and improve cell fate engineering with network biology
cn_clr R Documentation
make a CLR-like matrix for assessment purposes
Description
computes gene-gene correlation, then clr-like zscores
Usage
cn_clr(sampTab, expDat, species = "Mm", tfs = NA, grnSampSize = 40,
normDat = FALSE, dLevel = "description1")
Arguments
expDat
properly normalized expression matrix
tfs
vector of transcription factors
grnSampSize
min number of samples per ct or group
normDat
whether to quantile normalize the data prior to computing correlations
dLevel
column name in sample table to group samples by
samptTab
sample table
Value
zscore matrix
pcahan1/CellNet documentation built on May 18, 2023, 4:58 p.m.
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| cn_clr | R Documentation |
make a CLR-like matrix for assessment purposes
Description
computes gene-gene correlation, then clr-like zscores
Usage
cn_clr(sampTab, expDat, species = "Mm", tfs = NA, grnSampSize = 40,
normDat = FALSE, dLevel = "description1")
Arguments
expDat |
properly normalized expression matrix |
tfs |
vector of transcription factors |
grnSampSize |
min number of samples per ct or group |
normDat |
whether to quantile normalize the data prior to computing correlations |
dLevel |
column name in sample table to group samples by |
samptTab |
sample table |
Value
zscore matrix
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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