Mutant Identification through Probabilistic High throughput
Enabled NOrmalization
Description
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.