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TitanCNA
Subclonal copy number and LOH prediction from whole genome sequencing of tumours
Bioconductor version: 3.0
Hidden Markov model to segment and predict regions of subclonal copy number alterations (CNA) and loss of heterozygosity (LOH), and estimate cellular prevalenece of clonal clusters in tumour whole genome sequencing data.
Author: Gavin Ha, Sohrab P Shah
Maintainer: Gavin Ha <gavinha at gmail.com>, Sohrab P Shah <sshah at bccrc.ca>
Citation (from within R,
enter citation("TitanCNA")):
Installation
To install this package, start R and enter:
source("http://bioconductor.org/biocLite.R")
biocLite("TitanCNA")
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("TitanCNA")
| R Script | TitanCNA | |
| Reference Manual | ||
| Text | LICENSE |
Details
| biocViews | CopyNumberVariation, DNASeq, ExomeSeq, Genetics, GenomicVariation, HiddenMarkovModel, Sequencing, Software, StatisticalMethod, WholeGenome |
| Version | 1.4.0 |
| In Bioconductor since | BioC 2.14 (R-3.1) |
| License | file LICENSE |
| Depends | R (>= 3.1.0), foreach (>= 1.4.0), IRanges(>= 1.99.1), Rsamtools(>= 1.17.11), GenomeInfoDb(>= 1.1.3) |
| Imports | |
| 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 | TitanCNA_1.4.0.tar.gz |
| Windows Binary | TitanCNA_1.4.0.zip (32- & 64-bit) |
| Mac OS X 10.6 (Snow Leopard) | TitanCNA_1.4.0.tgz |
| Mac OS X 10.9 (Mavericks) | TitanCNA_1.4.0.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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