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Inverse normal transformation (INT) based genetic association testing. These tests are recommend for continuous traits with non-normally distributed residuals. INT-based tests robustly control the type I error in settings where standard linear regression does not, as when the residual distribution exhibits excess skew or kurtosis. Moreover, INT-based tests outperform standard linear regression in terms of power. These tests may be classified into two types. In direct INT (D-INT), the phenotype is itself transformed. In indirect INT (I-INT), phenotypic residuals are transformed. The omnibus test (O-INT) adaptively combines D-INT and I-INT into a single robust and statistically powerful approach. See McCaw ZR, Lane JM, Saxena R, Redline S, Lin X. "Operating characteristics of the rank-based inverse normal transformation for quantitative trait analysis in genome-wide association studies" <doi:10.1111/biom.13214>.

Type Size Name Uploaded Downloads Labels
conda 237.8 kB | linux-64/r-rnomni-1.0.1.2-r43h884c59f_0.tar.bz2  1 year and 1 month ago 25 main
conda 249.0 kB | linux-64/r-rnomni-1.0.0-r42h884c59f_0.tar.bz2  2 years and 7 months ago 56 main
conda 238.6 kB | win-64/r-rnomni-0.7.1-r36h796a38f_0.tar.bz2  4 years and 11 months ago 86 main
conda 262.2 kB | osx-64/r-rnomni-0.7.1-r36h466af19_0.tar.bz2  4 years and 11 months ago 17 main
conda 241.6 kB | linux-64/r-rnomni-0.7.1-r36h29659fb_0.tar.bz2  4 years and 11 months ago 94 main

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