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To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("RpsiXML")
In most cases, you don't need to download the package archive at all.
RpsiXML
R interface to PSI-MI 2.5 files
Bioconductor version: 2.14
Queries, data structure and interface to visualization of interaction datasets. This package inplements the PSI-MI 2.5 standard and supports up to now 8 databases. Further databases supporting PSI-MI 2.5 standard will be added continuously.
Author: Jitao David Zhang, Stefan Wiemann, Marc Carlson, with contributions from Tony Chiang
Maintainer: Jitao David Zhang <jitao_david.zhang at roche.com>
Citation (from within R,
enter citation("RpsiXML")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("RpsiXML")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("RpsiXML")
| R Script | Application Examples of RpsiXML package | |
| R Script | Reading PSI-25 XML files | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Infrastructure, Proteomics, Software |
| Version | 2.6.0 |
| In Bioconductor since | BioC 2.3 (R-2.8) |
| License | LGPL-3 |
| Depends | methods, annotate(>= 1.21.0), graph(>= 1.21.0), Biobase, RBGL(>= 1.17.0), XML (>= 2.4.0), hypergraph(>= 1.15.2), AnnotationDbi |
| Imports | |
| Suggests | org.Hs.eg.db, org.Mm.eg.db, org.Dm.eg.db, org.Rn.eg.db, org.Sc.sgd.db, hom.Hs.inp.db, hom.Mm.inp.db, hom.Dm.inp.db, hom.Rn.inp.db, hom.Sc.inp.db, Rgraphviz, ppiStats, ScISI |
| System Requirements | |
| URL | http://www.bioconductor.org |
| Depends On Me | ScISI |
| Imports Me | ScISI |
| Suggests Me |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | RpsiXML_2.6.0.tar.gz |
| Windows Binary | RpsiXML_2.6.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | RpsiXML_2.6.0.tgz |
| Mac OS X 10.9 (Mavericks) | RpsiXML_2.6.0.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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