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Bioinformatics Advances
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Bioinformatics Advances
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App-SpaM: phylogenetic placement of short reads without sequence alignment

Authors: Matthias Blanke; Burkhard Morgenstern;

App-SpaM: phylogenetic placement of short reads without sequence alignment

Abstract

AbstractMotivationPhylogenetic placement is the task of placing a query sequence of unknown taxonomic origin into a given phylogenetic tree of a set of reference sequences. A major field of application of such methods is, for example, the taxonomic identification of reads in metabarcoding or metagenomic studies. Several approaches to phylogenetic placement have been proposed in recent years. The most accurate of them requires a multiple sequence alignment of the references as input. However, calculating multiple alignments is not only time-consuming but also limits the applicability of these approaches.ResultsHerein, we propose Alignment-free phylogenetic placement algorithm based on Spaced-word Matches (App-SpaM), an efficient algorithm for the phylogenetic placement of short sequencing reads on a tree of a set of reference sequences. App-SpaM produces results of high quality that are on a par with the best available approaches to phylogenetic placement, while our software is two orders of magnitude faster than these existing methods. Our approach neither requires a multiple alignment of the reference sequences nor alignments of the queries to the references. This enables App-SpaM to perform phylogenetic placement on a broad variety of datasets.Availability and implementationThe source code of App-SpaM is freely available on Github at https://github.com/matthiasblanke/App-SpaM together with detailed instructions for installation and settings. App-SpaM is furthermore available as a Conda-package on the Bioconda channel.Contactmatthias.blanke@biologie.uni-goettingen.deSupplementary informationSupplementary data are available at Bioinformatics Advances online.

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Top 10%
Green
gold