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XRate: a fast prototyping, training and annotation tool for phylo-grammars.

Klosterman PS, Uzilov AV, Bendaña YR, Bradley RK, Chao S, Kosiol C, Goldman N, Holmes I - BMC Bioinformatics (2006)

Bottom Line: The grammar is specified in an external configuration file, allowing users to design new grammars, estimate rate parameters from training data and annotate multiple sequence alignments without the need to recompile code from source.We have used xrate to measure codon substitution rates and predict protein and RNA secondary structures.Our results demonstrate that xrate estimates biologically meaningful rates and makes predictions whose accuracy is comparable to that of more specialized tools.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Bioengineering, University of California, Berkeley CA, USA. petek@accesscom.com

ABSTRACT

Background: Recent years have seen the emergence of genome annotation methods based on the phylo-grammar, a probabilistic model combining continuous-time Markov chains and stochastic grammars. Previously, phylo-grammars have required considerable effort to implement, limiting their adoption by computational biologists.

Results: We have developed an open source software tool, xrate, for working with reversible, irreversible or parametric substitution models combined with stochastic context-free grammars. xrate efficiently estimates maximum-likelihood parameters and phylogenetic trees using a novel "phylo-EM" algorithm that we describe. The grammar is specified in an external configuration file, allowing users to design new grammars, estimate rate parameters from training data and annotate multiple sequence alignments without the need to recompile code from source. We have used xrate to measure codon substitution rates and predict protein and RNA secondary structures.

Conclusion: Our results demonstrate that xrate estimates biologically meaningful rates and makes predictions whose accuracy is comparable to that of more specialized tools.

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Scatter plot comparing true instantaneous rates with estimated rates from simulated data for the codon model benchmark (see Results and Discussion).
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Figure 10: Scatter plot comparing true instantaneous rates with estimated rates from simulated data for the codon model benchmark (see Results and Discussion).

Mentions: A scatter plot of true vs estimated rates allows a more detailed analysis (see figure 10). This plot shows the true instantaneous rates of M0 plotted versus the instantaneous rates estimated from data simulated from M0. If = the points would lie on the bisection line y = x. Thus the deviation of the points from the bisection line indicates how different the rates are.


XRate: a fast prototyping, training and annotation tool for phylo-grammars.

Klosterman PS, Uzilov AV, Bendaña YR, Bradley RK, Chao S, Kosiol C, Goldman N, Holmes I - BMC Bioinformatics (2006)

Scatter plot comparing true instantaneous rates with estimated rates from simulated data for the codon model benchmark (see Results and Discussion).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC1622757&req=5

Figure 10: Scatter plot comparing true instantaneous rates with estimated rates from simulated data for the codon model benchmark (see Results and Discussion).
Mentions: A scatter plot of true vs estimated rates allows a more detailed analysis (see figure 10). This plot shows the true instantaneous rates of M0 plotted versus the instantaneous rates estimated from data simulated from M0. If = the points would lie on the bisection line y = x. Thus the deviation of the points from the bisection line indicates how different the rates are.

Bottom Line: The grammar is specified in an external configuration file, allowing users to design new grammars, estimate rate parameters from training data and annotate multiple sequence alignments without the need to recompile code from source.We have used xrate to measure codon substitution rates and predict protein and RNA secondary structures.Our results demonstrate that xrate estimates biologically meaningful rates and makes predictions whose accuracy is comparable to that of more specialized tools.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Bioengineering, University of California, Berkeley CA, USA. petek@accesscom.com

ABSTRACT

Background: Recent years have seen the emergence of genome annotation methods based on the phylo-grammar, a probabilistic model combining continuous-time Markov chains and stochastic grammars. Previously, phylo-grammars have required considerable effort to implement, limiting their adoption by computational biologists.

Results: We have developed an open source software tool, xrate, for working with reversible, irreversible or parametric substitution models combined with stochastic context-free grammars. xrate efficiently estimates maximum-likelihood parameters and phylogenetic trees using a novel "phylo-EM" algorithm that we describe. The grammar is specified in an external configuration file, allowing users to design new grammars, estimate rate parameters from training data and annotate multiple sequence alignments without the need to recompile code from source. We have used xrate to measure codon substitution rates and predict protein and RNA secondary structures.

Conclusion: Our results demonstrate that xrate estimates biologically meaningful rates and makes predictions whose accuracy is comparable to that of more specialized tools.

Show MeSH