Mutant Identification through Probabilistic High throughput Enabled NOrmalization This package contains functions to carry out processing of high throughput data analysis and detection of putative hits/mutants. Contents include a function for post-hoc quality control for removal of outlier sample sets, a median-based normalization method for use in datasets where there are no explicit controls and where most of the responses are of the wildtype/no response class (see accompanying paper). The package also includes a way to prioritize individuals of interest using am empirical cumulative distribution function. Methods for generating synthetic data as well as data from the Chloroplast 2010 project are included. Software Depends: R (>= 2.12.1) Imports: doBy, gdata Shannon M. Bell <bell.shannonm@gmail.com> Shannon M. Bell <bell.shannonm@gmail.com>, Lyle D. Burgoon <burgoon.lyle@epa.gov> GPL (>= 3) 2012-01-27 application/tgz http://CRAN.R-project.org/package=MIPHENO