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LMAT | Scalable metagenomic taxonomy classification using a reference genome database

A method presented to shift computational costs to an offline computation by creating a taxonomy/genome index that supports scalable metagenomic classification. LMAT is designed to efficiently assign taxonomic labels to as many reads as possible in very large metagenomic datasets and report the taxonomic profile of the input sample. The quick 'single pass' analysis of every read allows to support additional more computationally expensive analysis such as metagenomic assembly or sensitive database searches on targeted subsets of reads.

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LMAT classification

LMAT specifications

Unique identifier:
Software type:
Restrictions to use:
Programming languages:
C++, Python
Livermore Metagenomics Analysis Toolkit
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
Computer skills:

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Center for Applied Scientific Computing, Livermore, CA, USA; Lawrence Livermore National Laboratory, Livermore, CA, USA; Global Security Directorate, Livermore, CA, USA

Funding source(s)

This work was supported by the Laboratory Directed Research and Development (33-ER-2012 and 08-ER-2011); DOE Office of Science (KJ0402000-SCW1076).

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