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A multiple testing procedure for testing several groups of hypotheses is implemented. Linear dependency among the hypotheses within the same group is modeled by using hidden Markov Models. It is noted that a smaller p value does not necessarily imply more significance due to the dependency. A typical application is to analyze genome wide association studies datasets, where SNPs from the same chromosome are treated as a group and exhibit strong linear genomic dependency. See Wei Z, Sun W, Wang K, Hakonarson H (2009) <doi:10.1093/bioinformatics/btp476> for more details.
Version: | 1.2 |
Published: | 2022-10-02 |
DOI: | 10.32614/CRAN.package.PLIS |
Author: | Zhi Wei & Wenguang Sun |
Maintainer: | Zhi Wei <zhiwei04 at gmail.com> |
License: | GPL-3 |
NeedsCompilation: | no |
CRAN checks: | PLIS results |
Reference manual: | PLIS.pdf |
Package source: | PLIS_1.2.tar.gz |
Windows binaries: | r-devel: PLIS_1.2.zip, r-release: PLIS_1.2.zip, r-oldrel: PLIS_1.2.zip |
macOS binaries: | r-release (arm64): PLIS_1.2.tgz, r-oldrel (arm64): PLIS_1.2.tgz, r-release (x86_64): PLIS_1.2.tgz, r-oldrel (x86_64): PLIS_1.2.tgz |
Old sources: | PLIS archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.