MIPHENO: Mutant Identification through Probabilistic High throughput Enabled NOrmalization
Version 1.2

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.

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AuthorShannon M. Bell <bell.shannonm@gmail.com>, Lyle D. Burgoon <burgoon.lyle@epa.gov>
Date of publication2012-01-27 11:27:41
MaintainerShannon M. Bell <bell.shannonm@gmail.com>
LicenseGPL (>= 3)
Version1.2
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("MIPHENO")

Man pages

cdf.pval: Generate Empirical pvalues from Cumulative Distribution...
find_hits: Identification of putative hits using Zvalues or MIPHENO...
mad.scores: Calculates the mad score (zscore)
rm.outliers: Post-Hoc outlier removal for high throughput data

Functions

cdf.pval Man page Source code
find_hits Man page Source code
mad.scores Man page Source code
rm.outliers Man page Source code

Files

MD5
R
R/rm.outliers.R
R/mad.scores.R
R/find_hits.R
R/cdf.pval.R
NAMESPACE
man
man/rm.outliers.Rd
man/mad.scores.Rd
man/find_hits.Rd
man/cdf.pval.Rd
DESCRIPTION
MIPHENO documentation built on May 19, 2017, 4:33 p.m.