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          Institute: MPI für Informatik     Collection: Computational Biology and Applied Algorithmics     Display Documents



ID: 428002.0, MPI für Informatik / Computational Biology and Applied Algorithmics
Rtreemix: an R package for estimating evolutionary pathways and genetic progression scores
Authors:Bogojeska, Jasmina; Alexa, Adrian; Altmann, André; Lengauer, Thomas; Rahnenführer, Jörg
Language:English
Date of Publication (YYYY-MM-DD):2008
Title of Journal:Bioinformatics
Volume:24
Issue / Number:20
Start Page:2391
End Page:2392
Copyright:© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative
Commons Attribution Non-Commercial License
(http://creativecommons.org/licenses/
by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and
reproduction in any medium, provided the original work is properly cited.
Review Status:Peer-review
Audience:Experts Only
Intended Educational Use:No
Abstract / Description:Summary: In genetics, many evolutionary pathways can be modeled by the ordered
accumulation of permanent changes. Mixture models of mutagenetic trees have
been used to describe disease progression in cancer and in HIV. In cancer,
progression is modeled by the accumulation of chromosomal gains and losses in
tumor cells; in HIV, the accumulation of drug resistance-associated mutations
in the viral genome is known to be associated with disease progression. From
such evolutionary models, genetic progression scores can be derived that assign
measures for the disease state to single patients. Rtreemix is an R package for
estimating mixture models of evolutionary pathways from observed
cross-sectional data and for estimating associated genetic progression scores.
The package also provides extended functionality for estimating confidence
intervals for estimated model parameters and for evaluating the stability of
the estimated evolutionary mixture models.
Last Change of the Resource (YYYY-MM-DD):2009-03-09
External Publication Status:published
Document Type:Article
Communicated by:Thomas Lengauer
Affiliations:MPI f�r Informatik/Computational Biology and Applied Algorithmics
Identifiers:LOCALID:C125756E0038A185-6B37EB33694127E1C125751200507021-...
URL:http://dx.doi.org/10.1093/bioinformatics/btn410
DOI:10.1093/bioinformatics/btn410
ISSN:1367-4803
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