Prediction of missing sequences and branch lengths in phylogenomic data | Zendy

Diego Darriba | Zendy; Michael Weiß | Zendy; Alexandros Stamatakis | Zendy

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Prediction of missing sequences and branch lengths in phylogenomic data

Author(s) -

Diego Darriba,

Michael Weiß,

Alexandros Stamatakis

Publication year - 2016

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btv768

Subject(s) - missing data , phylogenetic tree , sequence (biology) , inference , computer science , partition (number theory) , tree (set theory) , algorithm , data mining , biology , computational biology , artificial intelligence , mathematics , gene , genetics , machine learning , combinatorics

The presence of missing data in large-scale phylogenomic datasets has negative effects on the phylogenetic inference process. One effect that is caused by alignments with missing per-gene or per-partition sequences is that the inferred phylogenies may exhibit extremely long branch lengths. We investigate if statistically predicting missing sequences for organisms by using information from genes/partitions that have data for these organisms alleviates the problem and improves phylogenetic accuracy.

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