To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("gaucho")
In most cases, you don't need to download the package archive at all.
gaucho
Genetic Algorithms for Understanding Clonal Heterogeneity and Ordering
Bioconductor version: 3.0
Use genetic algorithms to determine the relationship between clones in heterogenous populations such as cancer sequencing samples
Author: Alex Murison [aut, cre], Christopher Wardell [aut, cre]
Maintainer: Alex Murison <Alexander.Murison at icr.ac.uk>, Christopher Wardell <Christopher.Wardell at icr.ac.uk>
Citation (from within R,
enter citation("gaucho")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("gaucho")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("gaucho")
| R Script | An introduction to gaucho | |
| Reference Manual | ||
| Text | NEWS |
Details
| biocViews | Genetics, SNP, Sequencing, Software, SomaticMutation |
| Version | 1.2.0 |
| In Bioconductor since | BioC 2.14 (R-3.1) |
| License | GPL-3 |
| Depends | R (>= 3.0.0), compiler, GA, graph, heatmap.plus, png, Rgraphviz |
| Imports | |
| LinkingTo | |
| Suggests | knitr |
| 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 | gaucho_1.2.0.tar.gz |
| Windows Binary | gaucho_1.2.0.zip |
| Mac OS X 10.6 (Snow Leopard) | gaucho_1.2.0.tgz |
| Mac OS X 10.9 (Mavericks) | gaucho_1.2.0.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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