期刊
METHODS IN ECOLOGY AND EVOLUTION
卷 13, 期 12, 页码 2699-2708出版社
WILEY
DOI: 10.1111/2041-210X.14006
关键词
environmental DNA (eDNA); lowest common ancestor (LCA); metagenomics; next-generation sequencing; sedimentary ancient DNA (sedaDNA); shotgun sequencing; taxonomic profiling; toolkit
类别
资金
- Carlsberg Foundation [CF16-0728, CF16-0913, CF18-0024, CF19-0712]
- Natural Environmental Research Council [NE/L002531/1]
ngsLCA is a command-line toolkit for obtaining taxonomic profiles from metagenomic data generated from environmental samples. It has flexible parameter settings, processes large datasets quickly, and provides methods for filtering, contamination removal, taxonomic clustering, and visualizing the generated taxonomic profiles.
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
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