Phylogeny Estimation Given Sequence Length Heterogeneity.

Systematic Biology
Vladimir Smirnov, Tandy Warnow

Abstract

Phylogeny estimation is a major step in many biological studies, and has many well known challenges. With the dropping cost of sequencing technologies, biologists now have increasingly large datasets available for use in phylogeny estimation. Here we address the challenge of estimating a tree given large datasets with a combination of full-length sequences and fragmentary sequences, which can arise due to a variety of reasons, including sample collection, sequencing technologies, and analytical pipelines. We compare two basic approaches: (1) computing an alignment on the full dataset and then computing a maximum likelihood tree on the alignment, or (2) constructing an alignment and tree on the full length sequences and then using phylogenetic placement to add the remaining sequences (which will generally be fragmentary) into the tree. We explore these two approaches on a range of simulated datasets, each with 1000 sequences and varying in rates of evolution, and two biological datasets. Our study shows some striking performance differences between methods, especially when there is substantial sequence length heterogeneity and high rates of evolution. We find in particular that using UPP to align sequences and RAxML to compute a...Continue Reading

Associated Datasets

Aug 20, 2020·Tandy Warnow, Vladimir Smirnov

References

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Apr 18, 2020·BMC Genomics·Vladimir Smirnov, Tandy Warnow

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Citations

Jul 29, 2021·Bioinformatics·Maya GuptaTandy Warnow
Aug 17, 2021·Systematic Biology·Joel O WertheimMichael J Sanderson

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Software Mentioned

SATé
TreeMerge
ROSE
Kalign3
RaxML
Guide Tree Merger
FastTree
pplacer
SEPP
RNASim2

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