Sign in
BioinformaticsBMC Bioinformatics
Peer-reviewed journal article

mtDNAcombine: tools to combine sequences from multiple studies

Eleanor F. MilleriD, Andrea ManicaiD

Abstract

Today an unprecedented amount of genetic sequence data is stored in publicly available repositories. For decades now, mitochondrial DNA (mtDNA) has been the workhorse of genetic studies, and as a result, there is a large volume of mtDNA data available in these repositories for a wide range of species. Indeed, whilst whole genome sequencing is an exciting prospect for the future, for most non-model organisms classical markers such as mtDNA remain widely used. By compiling existing data from multiple original studies, it is possible to build powerful new datasets capable of exploring many questions in ecology, evolution and conservation biology. One key question that these data can help inform is what happened in a species demographic past. However, compiling data in this manner is not trivial, there are many complexities associated with data extraction, data quality and data handling. Here we present the mtDNAcombine package, a collection of tools developed to manage some of the major decisions associated with handling multi-study sequence data with a particular focus on preparing mtDNA data for Bayesian Skyline Plot demographic reconstructions.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
1
FWCI
0.14
Field percentile
41th percentile

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.