MOTIVATION: Assays in mitochondrial genomics rely on accurate read mapping and variant calling. However, there are known and unknown nuclear paralogs that have fundamentally different genetic properties than that of the mitochondrial genome. Such paralogs complicate the interpretation of mitochondrial genome data and confound variant calling. RESULTS: Remove the Numts! (RtN!) was developed to categorize reads from massively parallel sequencing data not based on the expected properties and sequence identities of paralogous nuclear encoded mitochondrial sequences, but instead using sequence similarity to a large database of publicly available mitochondrial genomes. RtN! removes low-level sequencing noise and mitochondrial paralogs while not impacting variant calling, while competing methods were shown to remove true variants from mitochondrial mixtures. AVAILABILITY AND IMPLEMENTATION: https://github.com/Ahhgust/RtN. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: Assays in mitochondrial genomics rely on accurate read mapping and variant calling. However, there are known and unknown nuclear paralogs that have fundamentally different genetic properties than that of the mitochondrial genome. Such paralogs complicate the interpretation of mitochondrial genome data and confound variant calling. RESULTS: Remove the Numts! (RtN!) was developed to categorize reads from massively parallel sequencing data not based on the expected properties and sequence identities of paralogous nuclear encoded mitochondrial sequences, but instead using sequence similarity to a large database of publicly available mitochondrial genomes. RtN! removes low-level sequencing noise and mitochondrial paralogs while not impacting variant calling, while competing methods were shown to remove true variants from mitochondrial mixtures. AVAILABILITY AND IMPLEMENTATION: https://github.com/Ahhgust/RtN. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Utpal Smart; Jennifer Churchill Cihlar; Sammed N Mandape; Melissa Muenzler; Jonathan L King; Bruce Budowle; August E Woerner Journal: Genes (Basel) Date: 2021-01-20 Impact factor: 4.096
Authors: Cassandra R Taylor; Kevin M Kiesler; Kimberly Sturk-Andreaggi; Joseph D Ring; Walther Parson; Moses Schanfield; Peter M Vallone; Charla Marshall Journal: Genes (Basel) Date: 2020-10-29 Impact factor: 4.096
Authors: Filipe Cortes-Figueiredo; Filipa S Carvalho; Ana Catarina Fonseca; Friedemann Paul; José M Ferro; Sebastian Schönherr; Hansi Weissensteiner; Vanessa A Morais Journal: Int J Mol Sci Date: 2021-11-06 Impact factor: 5.923
Authors: Kimberly Sturk-Andreaggi; Joseph D Ring; Adam Ameur; Ulf Gyllensten; Martin Bodner; Walther Parson; Charla Marshall; Marie Allen Journal: Int J Mol Sci Date: 2022-02-17 Impact factor: 5.923