Quartet Based Gene Tree Imputation Using Deep Learning Improves Phylogenomic Analyses Despite Missing Data

Journal of computational biology: A journal of computational molecular cell biology

article

Sazan Mahbub¹  Shashata Sawmya¹  Arpita Saha¹  Rezwana Reaz¹  M. Sohel Rahman¹  Shamsuzzoha Bayzid¹ 

[1] Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology;Department of Computer Science, University of Maryland, College Park

关键词: gene tree;    gene tree discordance;    incomplete lineage sorting;    quartet consistency;    quartet distribution;    species tree;    missing data;    gene tree imputation;   

DOI  :  10.1089/cmb.2022.0212

学科分类：生物科学（综合）

来源: Mary Ann Liebert, Inc. Publishers

【 摘 要 】

Species tree estimation is frequently based on phylogenomic approaches that use multiple genes from throughout the genome. However, for a combination of reasons (ranging from sampling biases to more biological causes, as in gene birth and loss), gene trees are often incomplete, meaning that not all species of interest have a common set of genes. Incomplete gene trees can potentially impact the accuracy of phylogenomic inference. We, for the first time, introduce the problem of imputing the quartet distribution induced by a set of incomplete gene trees, which involves adding the missing quartets back to the quartet distribution. We present Quartet based Gene tree Imputation using Deep Learning (QT-GILD), an automated and specially tailored unsupervised deep learning technique, accompanied by cues from natural language processing, which learns the quartet distribution in a given set of incomplete gene trees and generates a complete set of quartets accordingly. QT-GILD is a general-purpose technique needing no explicit modeling of the subject system or reasons for missing data or gene tree heterogeneity. Experimental studies on a collection of simulated and empirical datasets suggest that QT-GILD can effectively impute the quartet distribution, which results in a dramatic improvement in the species tree accuracy. Remarkably, QT-GILD not only imputes the missing quartets but can also account for gene tree estimation error. Therefore, QT-GILD advances the state-of-the-art in species tree estimation from gene trees in the face of missing data.

【 授权许可】

Unknown