To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("IPPD")
In most cases, you don't need to download the package archive at all.
IPPD
Isotopic peak pattern deconvolution for Protein Mass Spectrometry by template matching
Bioconductor version: 3.0
The package provides functionality to extract isotopic peak patterns from raw mass spectra. This is done by fitting a large set of template basis functions to the raw spectrum using either nonnegative least squares or least absolute deviation fittting. The package offers a flexible function which tries to estimate model parameters in a way tailored to the peak shapes in the data. The package also provides functionality to process LCMS runs.
Author: Martin Slawski <ms at cs.uni-saarland.de>, Rene Hussong <rene.hussong at uni.lu>, Andreas Hildebrandt <andreas.hildebrandt at uni-mainz.de>, Matthias Hein <hein at cs.uni-saarland.de>
Maintainer: Martin Slawski <ms at cs.uni-saarland.de>
Citation (from within R,
enter citation("IPPD")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("IPPD")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("IPPD")
| R Script | IPPD Manual | |
| Reference Manual |
Details
| biocViews | Proteomics, Software |
| Version | 1.14.0 |
| In Bioconductor since | BioC 2.8 (R-2.13) |
| License | GPL (version 2 or later) |
| Depends | R (>= 2.12.0), MASS, Matrix, XML, digest, bitops |
| Imports | methods, stats, graphics |
| LinkingTo | |
| Suggests | |
| SystemRequirements | |
| Enhances | |
| URL | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | RforProteomics |
| Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Package Source | IPPD_1.14.0.tar.gz |
| Windows Binary | IPPD_1.14.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | IPPD_1.14.0.tgz |
| Mac OS X 10.9 (Mavericks) | IPPD_1.14.0.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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