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

Linking:

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