fastcmh: Significant Interval Discovery with Categorical Covariates

A method which uses the Cochran-Mantel-Haenszel test with significant pattern mining to detect intervals in binary genotype data which are significantly associated with a particular phenotype, while accounting for categorical covariates.

Version: 0.2.7
Depends: R (≥ 3.3.0), bindata
Imports: Rcpp
LinkingTo: Rcpp
Suggests: testthat
Published: 2016-09-13
Author: Felipe Llinares Lopez, Dean Bodenham
Maintainer: Dean Bodenham <deanbodenhambsse at gmail.com>
License: GPL-2 | GPL-3
NeedsCompilation: yes
SystemRequirements: C++11
CRAN checks: fastcmh results

Documentation:

Reference manual: fastcmh.pdf

Downloads:

Package source: fastcmh_0.2.7.tar.gz
Windows binaries: r-devel: fastcmh_0.2.7.zip, r-release: fastcmh_0.2.7.zip, r-oldrel: fastcmh_0.2.7.zip
macOS binaries: r-release (arm64): fastcmh_0.2.7.tgz, r-oldrel (arm64): fastcmh_0.2.7.tgz, r-release (x86_64): fastcmh_0.2.7.tgz, r-oldrel (x86_64): fastcmh_0.2.7.tgz
Old sources: fastcmh archive

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