GetOrganelle: A fast and versatile toolkit for accurate de novo assembly of organelle genomes

Jian Jun Jin, Wen Bin Yu, Jun Bo Yang, Yu Song, Claude W. Depamphilis, Ting Shuang Yi, De Zhu Li

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

GetOrganelle is a state-of-the-art toolkit to accurately assemble organelle genomes from whole genome sequencing data. It recruits organelle-associated reads using a modified "baiting and iterative mapping"approach, conducts de novo assembly, filters and disentangles the assembly graph, and produces all possible configurations of circular organelle genomes. For 50 published plant datasets, we are able to reassemble the circular plastomes from 47 datasets using GetOrganelle. GetOrganelle assemblies are more accurate than published and/or NOVOPlasty-reassembled plastomes as assessed by mapping. We also assemble complete mitochondrial genomes using GetOrganelle. GetOrganelle is freely released under a GPL-3 license (https://github.com/Kinggerm/GetOrganelle).

Original languageEnglish (US)
Article number241
JournalGenome biology
Volume21
Issue number1
DOIs
StatePublished - Sep 10 2020

All Science Journal Classification (ASJC) codes

  • Ecology, Evolution, Behavior and Systematics
  • Genetics
  • Cell Biology

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