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source("http://bioconductor.org/biocLite.R")
biocLite("HybridMTest")
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HybridMTest
Hybrid Multiple Testing
Bioconductor version: 2.14
Performs hybrid multiple testing that incorporates method selection and assumption evaluations into the analysis using empirical Bayes probability (EBP) estimates obtained by Grenander density estimation. For instance, for 3-group comparison analysis, Hybrid Multiple testing considers EBPs as weighted EBPs between F-test and H-test with EBPs from Shapiro Wilk test of normality as weigth. Instead of just using EBPs from F-test only or using H-test only, this methodology combines both types of EBPs through EBPs from Shapiro Wilk test of normality. This methodology uses then the law of total EBPs.
Author: Stan Pounds <stanley.pounds at stjude.org>, Demba Fofana <demba.fofana at stjude.org>
Maintainer: Demba Fofana <demba.fofana at stjude.org>
Citation (from within R,
enter citation("HybridMTest")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("HybridMTest")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("HybridMTest")
| R Script | Hybrid Multiple Testing | |
| Reference Manual |
Details
| biocViews | GeneExpression, Genetics, Microarray, Software |
| Version | 1.8.0 |
| In Bioconductor since | BioC 2.10 (R-2.15) |
| License | GPL Version 2 or later |
| Depends | R (>= 2.9.0), Biobase, fdrtool, MASS, survival |
| Imports | stats |
| Suggests | |
| System Requirements | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | HybridMTest_1.8.0.tar.gz |
| Windows Binary | HybridMTest_1.8.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | HybridMTest_1.8.0.tgz |
| Mac OS X 10.9 (Mavericks) | HybridMTest_1.8.0.tgz |
| Browse/checkout source | (username/password: readonly) |
| Package Downloads Report | Download Stats |
Common Bioconductor workflows include:
- Oligonucleotide Arrays
- High-throughput Sequencing
- Counting Reads for Differential Expression (parathyroideSE vignette)
- Annotation
- Annotating Variants
- Annotating Ranges
- Flow Cytometry and other assays
- Candidate Binding Sites for Known Transcription Factors
- Cloud-enabled cis-eQTL search and annotation
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