gDist: Density/Distribution Plot for gPCA
In gPCA: Batch Effect Detection via Guided Principal Components Analysis
Description
Usage
Arguments
Author(s)
References
See Also
Examples
Description
This function produces a density plot of the permutation δ_p values.
Usage
1
gDist(out)
Arguments
out
object resulting from gPCA.batchdetect() call.
Author(s)
Sarah Reese reesese@vcu.edu
References
Reese, S. E., Archer, K. J., Therneau, T. M., Atkinson, E. J., Vachon, C. M., de Andrade, M., Kocher, J. A., and Eckel-Passow, J. E. A new statistic for identifying batch effects in high-throughput genomic data that uses guided principal components analysis. Bioinformatics, (in review).
See Also
gPCA.batchdetect,PCplot,CumulativeVarPlot
Examples
1
# gDist(out)
Example output
gPCA documentation built on May 2, 2019, 4:02 p.m.
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Description Usage Arguments Author(s) References See Also Examples
Description
This function produces a density plot of the permutation δ_p values.
Usage
1 | gDist(out)
|
Arguments
out |
object resulting from |
Author(s)
Sarah Reese reesese@vcu.edu
References
Reese, S. E., Archer, K. J., Therneau, T. M., Atkinson, E. J., Vachon, C. M., de Andrade, M., Kocher, J. A., and Eckel-Passow, J. E. A new statistic for identifying batch effects in high-throughput genomic data that uses guided principal components analysis. Bioinformatics, (in review).
See Also
gPCA.batchdetect,PCplot,CumulativeVarPlot
Examples
1 | # gDist(out)
|
Example output
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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