To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("LPEadj")
In most cases, you don't need to download the package archive at all.
LPEadj
A correction of the local pooled error (LPE) method to replace the asymptotic variance adjustment with an unbiased adjustment based on sample size.
Bioconductor version: 3.0
Two options are added to the LPE algorithm. The original LPE method sets all variances below the max variance in the ordered distribution of variances to the maximum variance. in LPEadj this option is turned off by default. The second option is to use a variance adjustment based on sample size rather than pi/2. By default the LPEadj uses the sample size based variance adjustment.
Author: Carl Murie <carl.murie at mcgill.ca>, Robert Nadon <robert.nadon at mcgill.ca>
Maintainer: Carl Murie <carl.murie at mcgill.ca>
Citation (from within R,
enter citation("LPEadj")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("LPEadj")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("LPEadj")
| R Script | LPEadj test for microarray data with small number of replicates | |
| Reference Manual |
Details
| biocViews | Microarray, Proteomics, Software |
| Version | 1.26.0 |
| In Bioconductor since | BioC 2.3 (R-2.8) |
| License | LGPL |
| Depends | LPE |
| Imports | LPE, stats |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | LPEadj_1.26.0.tar.gz |
| Windows Binary | LPEadj_1.26.0.zip |
| Mac OS X 10.6 (Snow Leopard) | LPEadj_1.26.0.tgz |
| Mac OS X 10.9 (Mavericks) | LPEadj_1.26.0.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
- RNA-Seq workflow: gene-level exploratory analysis and differential expression
- Changing genomic coordinate systems with rtracklayer::liftOver
- Mass spectrometry and proteomics data analysis
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