Estimation of Interpretable eQTL Effect Sizes Using a Log of Linear Model
Released Mar 11, 2017 by Andrey A Shabalin, John Palowitch
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.
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<dependencies> <dependency> <groupId>org.renjin.cran</groupId> <artifactId>ACMEeqtl</artifactId> <version>1.4-b14</version> </dependency> </dependencies> <repositories> <repository> <id>bedatadriven</id> <name>bedatadriven public repo</name> <url>https://nexus.bedatadriven.com/content/groups/public/</url> </repository> </repositories>
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This package was last tested against Renjin 0.8.2431 on Sep 20, 2017.