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) .


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1.6 by Andrey A Shabalin, a year ago

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Authors: Andrey A Shabalin [aut, cre] , John Palowitch [aut]

Documentation:   PDF Manual  

LGPL-3 license

Imports parallel

Depends on filematrix

Suggests knitr, rmarkdown, pander

See at CRAN