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.
| Version: | 1.4 |
| Depends: | R (≥ 3.3.0), filematrix |
| Imports: | parallel |
| Suggests: | knitr, rmarkdown, BiocStyle, pander |
| Published: | 2017-03-11 |
| Author: | Andrey A Shabalin, John Palowitch |
| 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 |
| Reference manual: | ACMEeqtl.pdf |
| Vignettes: |
ACMEeqtl Overview |
| Package source: | ACMEeqtl_1.4.tar.gz |
| Windows binaries: | r-devel: ACMEeqtl_1.4.zip, r-release: ACMEeqtl_1.4.zip, r-oldrel: ACMEeqtl_1.4.zip |
| OS X El Capitan binaries: | r-release: ACMEeqtl_1.4.tgz |
| OS X Mavericks binaries: | r-oldrel: ACMEeqtl_1.4.tgz |
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