ACMEeqtl: Estimation of Interpretable eQTL Effect Sizes Using a Log of Linear Model

We use a non-linear model, termed ACME, that reflects a parsimonious biological model for allelic contributions of cis-acting eQTLs. With non-linear least-squares algorithm we estimate maximum likelihood parameters. The ACME model provides interpretable effect size estimates and p-values with well controlled Type-I error. Includes both R and (much faster) C implementations. For more details see Palowitch et al. (2017) <doi:10.1111/biom.12810>.

Version: 1.5
Depends: R (≥ 3.3.0), filematrix
Imports: parallel
Suggests: knitr, rmarkdown, BiocStyle, pander
Published: 2018-01-13
Author: Andrey A Shabalin ORCID iD [aut, cre], John Palowitch ORCID iD [aut]
Maintainer: Andrey A Shabalin <andrey.shabalin at gmail.com>
BugReports: https://github.com/andreyshabalin/ACMEeqtl/issues
License: LGPL-3
URL: https://github.com/andreyshabalin/ACMEeqtl
NeedsCompilation: yes
Citation: ACMEeqtl citation info
CRAN checks: ACMEeqtl results

Downloads:

Reference manual: ACMEeqtl.pdf
Vignettes: ACMEeqtl Overview Vignette
Package source: ACMEeqtl_1.5.tar.gz
Windows binaries: r-devel: ACMEeqtl_1.5.zip, r-release: ACMEeqtl_1.5.zip, r-oldrel: ACMEeqtl_1.5.zip
OS X El Capitan binaries: r-release: ACMEeqtl_1.5.tgz
OS X Mavericks binaries: r-oldrel: ACMEeqtl_1.4.tgz
Old sources: ACMEeqtl archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ACMEeqtl to link to this page.