tnsStratification: Sample stratification for a TNS object
In csgroen/RTNsurvival: Survival analysis using transcriptional networks inferred by the RTN package
Description
Usage
Arguments
Value
See Also
Examples
Description
Internal function, used for sample stratification.
Usage
1
tnsStratification(tns, nSections = 1, center = FALSE)
Arguments
tns
a TNS object, which must have passed GSEA2 analysis.
nSections
A numeric value for the stratification of the sample. The
larger the number, the more subdivisions will be created for the Kaplan-Meier
analysis.
center
a logical value. If TRUE, numbers assigned to each group is
centralized on regulon activity scale.
Value
An updated TNS object.
See Also
Examples
1
# see tnsKM method.
csgroen/RTNsurvival documentation built on May 20, 2019, 1:49 p.m.
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Description Usage Arguments Value See Also Examples
Description
Internal function, used for sample stratification.
Usage
1 | tnsStratification(tns, nSections = 1, center = FALSE)
|
Arguments
tns |
a TNS object, which must have passed GSEA2 analysis. |
nSections |
A numeric value for the stratification of the sample. The larger the number, the more subdivisions will be created for the Kaplan-Meier analysis. |
center |
a logical value. If TRUE, numbers assigned to each group is centralized on regulon activity scale. |
Value
An updated TNS object.
See Also
Examples
1 | # see tnsKM method.
|
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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