Statistical issues associated with modeling of synonymous mutation data
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Snehalata Huzurbazar
,
Sarabdeep Singh
Abstract
The explosion of data in evolutionary bioinformatics has led to sometimes ad hoc, incomplete and even inaccurate data analyses. Taking dS data, namely, data on synonymous substitutions per synonymous sites, we go through a statistical analysis for modeling the time since duplications of genes. We explore the shortcomings of previous analyses, especially with a view towards their effect on inference for the gene duplication process. We present a statistical analysis which respects the assumptions of the models and the integrity of the data, and emphasize that exploratory data analysis, formulation of a data model, its estimation and finally, assessment of the model are important steps in a complete data analysis. Furthermore, for dS data, we develop Bayesian discrete-continuous mixture models and present analyses using two genomes.
The three authors’ research was supported by a grant to the University of Wyoming from the National Science Foundation under grant DMS-1100615. Huzurbazar’s contribution was also based upon work partially supported by the National Science Foundation under Grant DMS-1127914 to the Statistical and Applied Mathematical Sciences Institute. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. Huzurbazar and Singh thank David Liberles and Anke Konrad for introducing them to the study of gene duplications and evolutionary bioinformatics in general. All the authors thank the associate editor Vincent Plagnol and two anonymous reviewers for very helpful suggestions.
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©2013 by Walter de Gruyter Berlin Boston
Artikel in diesem Heft
- Masthead
- Masthead
- Review
- Genetic model selection in genome-wide association studies: robust methods and the use of meta-analysis
- Research Articles
- Hierarchical Bayesian mixture modelling for antigen-specific T-cell subtyping in combinatorially encoded flow cytometry studies
- An extension of the Wilcoxon-Mann-Whitney test for analyzing RT-qPCR data
- Block-diagonal discriminant analysis and its bias-corrected rules
- Statistical issues associated with modeling of synonymous mutation data
- Sensitivity to prior specification in Bayesian genome-based prediction models
- Bayesian hierarchical graph-structured model for pathway analysis using gene expression data
Artikel in diesem Heft
- Masthead
- Masthead
- Review
- Genetic model selection in genome-wide association studies: robust methods and the use of meta-analysis
- Research Articles
- Hierarchical Bayesian mixture modelling for antigen-specific T-cell subtyping in combinatorially encoded flow cytometry studies
- An extension of the Wilcoxon-Mann-Whitney test for analyzing RT-qPCR data
- Block-diagonal discriminant analysis and its bias-corrected rules
- Statistical issues associated with modeling of synonymous mutation data
- Sensitivity to prior specification in Bayesian genome-based prediction models
- Bayesian hierarchical graph-structured model for pathway analysis using gene expression data
