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.
|Author||Shannon M. Bell <email@example.com>, Lyle D. Burgoon <firstname.lastname@example.org>|
|Date of publication||2012-01-27 11:27:41|
|Maintainer||Shannon M. Bell <email@example.com>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
|Installation||Install the latest version of this package by entering the following in R:
|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|
|cdf.pval||Man page Source code|
|find_hits||Man page Source code|
|mad.scores||Man page Source code|
|rm.outliers||Man page Source code|
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