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Wiley, Methods in Ecology and Evolution, 12(13), p. 2699-2708, 2022

DOI: 10.1111/2041-210x.14006

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ngsLCA—A toolkit for fast and flexible lowest common ancestor inference and taxonomic profiling of metagenomic data

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Abstract Metagenomic data generated from environmental samples is increasingly common in the analysis of modern and ancient biological communities. To obtain taxonomic profiles from this type of data, DNA sequences are aligned against large genomic reference databases and the lowest common ancestor (LCA) needs to be inferred for each sequence with multiple alignments. To date, efforts have mainly focused on improving the speed, sensitivity and specificity of alignment tools, and little effort has been applied to the LCA algorithm that generates the taxonomic profiles from alignments. We present ngsLCA, a command‐line toolkit with two separate modules: the main program (in C/C++) performing LCA inference, and an R package for generating tables and visualisations of the taxonomic profiles. ngsLCA processed large datasets in BAM/SAM alignment format 4–11 times faster and used less memory compared to other available programs. It is compatible with the NCBI taxonomy and has flexible parameter settings. Furthermore, the toolkit offers functions for filtering, contamination removal, taxonomic clustering, and multiple ways of visualising the generated taxonomic profiles. ngsLCA bridges a gap in current metagenomic analyses by supplying a computationally light, easy‐to‐use, accurate, fast and flexible LCA algorithm with R functions for processing and illustrating the taxonomic profiles