Statistical binning leads to profound model violation due to gene tree error incurred by trying to avoid gene tree error

Molecular Phylogenetics and Evolution
Richard H Adams, Todd A Castoe

Abstract

Fundamental to all phylogenomic studies is the notion that increasing the amount of data - to entire genomes when possible - will increase the accuracy of phylogenetic inference. Simply adding more data does not, however, guarantee phylogenomic inferences will be more accurate. Even genome-scale reconstructions of species histories can suffer the effects of both incomplete lineage sorting (ILS) and gene tree estimation error (GTEE). Weighted statistical binning was originally proposed as a technique to assist the avian phylogenomics project in solving the bird tree of life, which has long eluded resolution as a result of both ILS and GTEE. These so-called "statistical binning procedures" seek to overcome GTEE by concatenating loci into longer multi-locus "supergenes" that are used to reconstruct a species tree under the assumption that the supergene tree set is an accurate estimate of the true underlying gene tree distribution. Here we evaluate the performance of the method using the original avian phylogenomics dataset. Our results suggest that statistical binning constructs false supergenes that concatenate loci with different coalescent histories more often than not: >92% of supergenes comprise discordant loci. Our results u...Continue Reading

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Citations

Aug 5, 2020·Systematic Biology·Matthew H Van DamMichelle Trautwein
Nov 25, 2020·BMC Evolutionary Biology·Bonnie B BlaimerMatthew L Buffington
Dec 29, 2020·Systematic Biology·Silas BossertBryan N Danforth
Oct 15, 2020·Bioinformatics·Richard H AdamsMichael DeGiorgio

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