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Genetic distance for a general non-stationary markov substitution process.

Kaehler BD, Yap VB, Zhang R, Huttley GA - Syst. Biol. (2014)

Bottom Line: Our measure of genetic distance reduces to the standard formulation if the data in question are consistent with the stationarity assumption.The magnitude of the distance bias is proportional to departure from stationarity, which we demonstrate to be associated with longer edge lengths.The marked improvement in consistency between the general nonstationary Markov model and sequence alignments leads us to conclude that analyses of evolutionary rates and phylogenies will be substantively improved by application of this model.

View Article: PubMed Central - PubMed

Affiliation: John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2600, Australia; and.

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GTR and GTR models overestimate departures from the molecular clock. Scatter plots of the ratio of mouse and human edge lengths measured as  or  against  from 3906 alignments of human, mouse, and opossum protein coding genes. All General model fits have goodness-of-fit . Plots were truncated near six; distance estimates greater than 100 were rejected as outliers. The curved lines show LOESS fits. Straight lines show the diagonal.
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Figure 9: GTR and GTR models overestimate departures from the molecular clock. Scatter plots of the ratio of mouse and human edge lengths measured as or against from 3906 alignments of human, mouse, and opossum protein coding genes. All General model fits have goodness-of-fit . Plots were truncated near six; distance estimates greater than 100 were rejected as outliers. The curved lines show LOESS fits. Straight lines show the diagonal.

Mentions: Figure 9 illustrates a more direct comparison, where we plot the ratio of between mouse and human edges to the ratio of and between mouse and human edges. There is a tendency for the length of the mouse edge to exceed that of the human edge by a greater amount under both the GTR and GTR models. In other words, the speedup of substitution rates on the mouse lineage is overstated by the stationary models.


Genetic distance for a general non-stationary markov substitution process.

Kaehler BD, Yap VB, Zhang R, Huttley GA - Syst. Biol. (2014)

GTR and GTR models overestimate departures from the molecular clock. Scatter plots of the ratio of mouse and human edge lengths measured as  or  against  from 3906 alignments of human, mouse, and opossum protein coding genes. All General model fits have goodness-of-fit . Plots were truncated near six; distance estimates greater than 100 were rejected as outliers. The curved lines show LOESS fits. Straight lines show the diagonal.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4380038&req=5

Figure 9: GTR and GTR models overestimate departures from the molecular clock. Scatter plots of the ratio of mouse and human edge lengths measured as or against from 3906 alignments of human, mouse, and opossum protein coding genes. All General model fits have goodness-of-fit . Plots were truncated near six; distance estimates greater than 100 were rejected as outliers. The curved lines show LOESS fits. Straight lines show the diagonal.
Mentions: Figure 9 illustrates a more direct comparison, where we plot the ratio of between mouse and human edges to the ratio of and between mouse and human edges. There is a tendency for the length of the mouse edge to exceed that of the human edge by a greater amount under both the GTR and GTR models. In other words, the speedup of substitution rates on the mouse lineage is overstated by the stationary models.

Bottom Line: Our measure of genetic distance reduces to the standard formulation if the data in question are consistent with the stationarity assumption.The magnitude of the distance bias is proportional to departure from stationarity, which we demonstrate to be associated with longer edge lengths.The marked improvement in consistency between the general nonstationary Markov model and sequence alignments leads us to conclude that analyses of evolutionary rates and phylogenies will be substantively improved by application of this model.

View Article: PubMed Central - PubMed

Affiliation: John Curtin School of Medical Research, Australian National University, Canberra, ACT, 2600, Australia; and.

Show MeSH
Related in: MedlinePlus