To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("PADOG")
In most cases, you don't need to download the package archive at all.
PADOG
Pathway Analysis with Down-weighting of Overlapping Genes (PADOG)
Bioconductor version: 3.0
This package implements a general purpose gene set analysis method called PADOG that downplays the importance of genes that apear often accross the sets of genes to be analyzed. The package provides also a benchmark for gene set analysis methods in terms of sensitivity and ranking using 24 public datasets from KEGGdzPathwaysGEO package.
Author: Adi Laurentiu Tarca <atarca at med.wayne.edu>
Maintainer: Adi Laurentiu Tarca <atarca at med.wayne.edu>
Citation (from within R,
enter citation("PADOG")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("PADOG")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("PADOG")
| R Script | PADOG | |
| Reference Manual |
Details
| biocViews | Microarray, OneChannel, Software, TwoChannel |
| Version | 1.8.0 |
| In Bioconductor since | BioC 2.11 (R-2.15) |
| License | GPL (>= 2) |
| Depends | R (>= 2.14.0), KEGGdzPathwaysGEO, graphics, limma, AnnotationDbi, Biobase, methods, nlme, GSA, KEGG.db |
| Imports | graphics, limma, hgu133plus2.db, hgu133a.db, KEGG.db, AnnotationDbi, Biobase, methods, nlme |
| LinkingTo | |
| Suggests | parallel |
| 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 | PADOG_1.8.0.tar.gz |
| Windows Binary | PADOG_1.8.0.zip |
| Mac OS X 10.6 (Snow Leopard) | PADOG_1.8.0.tgz |
| Mac OS X 10.9 (Mavericks) | PADOG_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
- 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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