The AssayCorrector eliminates spatial bias in HTS assays using PMP methods.
Switch branches/tags
Nothing to show
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Failed to load latest commit information.
R
data
hooks
info
man
.Rbuildignore
.gitignore
.travis.yml
AssayCorrector.Rproj
AssayCorrector.pdf
DESCRIPTION
HEAD
NAMESPACE
Readme.md
config

Readme.md

AssayCorrector

Build Status

Description

This package uses partial mean polish and non-parametric statistical procedures to identify and correct spatial bias present in high-thoughput screening assays.

Installation

You can install the AssayCorrector package by typing

install.packages('devtools')
devtools::install_github('ArtificialBreeze/AssayCorrector')

Usage

First, an assay object should be created by using

library(AssayCorrector)
# Fictive 8x12x5 assay
assay<-create_assay(m)
# Plate 7 taken from Carralot et al. 2012
assay<-create_assay(plate7)

Next, we can detect and correct the bias as follows:

detected<-detect_bias(assay,type="P",alpha=0.01)
corrected<-correct_bias(detected,method=1,type="P") # Correct the bias assuming an additive model (method=1), plate-wise only

The S3 methods print.assay() and plot.assay() override the default functions. Consult the complete pdf documentation for examples