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A random-forest-based approach for imputing clustered incomplete data

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MixRF

A random-forest-based approach for imputing clustered incomplete data

This R package offers random-forest-based functions to impute clustered incomplete data. The package is tailored for but not limited to imputing multitissue expression data, in which a gene's expression is measured on the collected tissues of an individual but missing on the uncollected tissues.

Installation

  • For the stable version from CRAN:
install.packages('MixRF')
  • For the development version (requiring the devtools package):
devtools::install_github('randel/MixRF')

Reference

Wang, J., Gamazon, E. R., Pierce, B. L., Stranger B. E., Im, H. K., Gibbons, R. D., Cox, N. J., Nicolae, D. L., & Chen, L. S. (2016). Imputing Gene Expression in Uncollected Tissues Within and Beyond GTEx. American Journal of Human Genetics. http://dx.doi.org/10.1016/j.ajhg.2016.02.020

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A random-forest-based approach for imputing clustered incomplete data

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