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Liftoff: accurate mapping of gene annotations

Alaina Shumate, Steven L. Salzberg

2020Bioinformatics1,088 citationsDOIOpen Access PDF

Abstract

MOTIVATION: Improvements in DNA sequencing technology and computational methods have led to a substantial increase in the creation of high-quality genome assemblies of many species. To understand the biology of these genomes, annotation of gene features and other functional elements is essential; however, for most species, only the reference genome is well-annotated. RESULTS: One strategy to annotate new or improved genome assemblies is to map or 'lift over' the genes from a previously annotated reference genome. Here, we describe Liftoff, a new genome annotation lift-over tool capable of mapping genes between two assemblies of the same or closely related species. Liftoff aligns genes from a reference genome to a target genome and finds the mapping that maximizes sequence identity while preserving the structure of each exon, transcript and gene. We show that Liftoff can accurately map 99.9% of genes between two versions of the human reference genome with an average sequence identity >99.9%. We also show that Liftoff can map genes across species by successfully lifting over 98.3% of human protein-coding genes to a chimpanzee genome assembly with 98.2% sequence identity. AVAILABILITY AND IMPLEMENTATION: Liftoff can be installed via bioconda and PyPI. In addition, the source code for Liftoff is available at https://github.com/agshumate/Liftoff. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Topics & Concepts

Computer scienceSoftwareComputational biologyArtificial intelligenceBiologyProgramming languageGenomics and Phylogenetic StudiesGenomics and Chromatin DynamicsGenomics and Rare Diseases
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