To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("flagme")
In most cases, you don't need to download the package archive at all.
flagme
Analysis of Metabolomics GC/MS Data
Bioconductor version: 3.0
Fragment-level analysis of gas chromatography - mass spectrometry metabolomics data
Author: Mark Robinson <mark.robinson at imls.uzh.ch>
Maintainer: Mark Robinson <mark.robinson at imls.uzh.ch>, Riccardo Romoli <riccardo.romoli at unifi.it>
Citation (from within R,
enter citation("flagme")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("flagme")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("flagme")
| R Script | Using flagme -- Fragment-level analysis of GCMS-based metabolomics data | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | DifferentialExpression, MassSpectrometry, Software |
| Version | 1.22.0 |
| In Bioconductor since | BioC 2.4 (R-2.9) |
| License | LGPL (>= 2) |
| Depends | gcspikelite, xcms, CAMERA |
| Imports | gplots, graphics, MASS, methods, SparseM, stats, utils |
| 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 | flagme_1.22.0.tar.gz |
| Windows Binary | flagme_1.22.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | flagme_1.22.0.tgz |
| Mac OS X 10.9 (Mavericks) | flagme_1.22.0.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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