Bivariate segmentation of SNP array data for allele-specific copy number analysis

CnaStruct version: Release (1.0)

CnaStruct is a bivariate segmentation method designed for allele-specific copy number analysis on SNP arrays. It is based on the structural change model (SCM) segmentation and is designed to correctly detect all changes in mean, whether they occur in a single variable (LRR or BAF) or both variables.

Author, mantainer: D. Mosén-Ansorena

To install this package, regardless of the operating system, enter in R:

    install.packages("CnaStruct_1.0.tar.gz", repos=NULL, type="source")

To use this package, enter:

    breakpoints(lrr.vector, baf.vector, beta=1, p=0.25, s=1, maxseg=500, maxk=500)

* BAF and LRR to segment are represented as common R vectors
* beta is the factor that regulates the importance of BAF with respect to LRR (greater beta, greater BAF importance)
* p is the Minkowski order (see paper)
* s is a penalisation factor (default value of 1 corresponds to BIC penalisation)
* maxseg and maxk limit the maximum segment number and their minimum length, respectively (use them to limit CPU time and RAM)

Change log

Version 1.0

  • Initial release: only for use on individual sequences (e.g. chromosomal arms).

Examples »

In this file you will find some quick examples.

Quick examples  

Contact »

You can contact me for any questions (including how to couple CnaStruct with methods such as GAP, ASCAT and TAPS), found bugs and suggestions at the following direction: _at_ cicbiogune _dot_ es

Bioconductor - open source software for bioinformatics