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Generating Heterogeneous Data on Gene Trees

Authors: Cortada García, Martí; Diéguez Moscardó, Adrià; Casanellas Rius, Marta; Cortada Garcia, Martí;

Generating Heterogeneous Data on Gene Trees

Abstract

We introduce GenPhylo, a Python module that simulates nucleotide sequence data along a phylogeny avoiding the restriction of continuous-time Markov processes. GenPhylo uses directly a general Markov model and therefore naturally incorporates heterogeneity across lineages. We solve the challenge of generating transition matrices with a pre-given expected number of substitutions (the branch length information) by providing an algorithm that can be incorporated in other simulation software.

to appear in Journal of Computational Biology

Keywords

Sequence data simulation, Àrees temàtiques de la UPC::Matemàtiques i estadística::Probabilitat, 92-10, Branch length, Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica, FOS: Biological sciences, Populations and Evolution (q-bio.PE), Nucleotide substitution, Quantitative Biology - Populations and Evolution

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green