Main logo
?
tutorial arrow
×
Create your own tool library
Bookmark tools and put favorites into folders to find them easily.

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.

User report

tutorial arrow
×
Vote up tools and offer feedback
Give value to tools and make your expertise visible
Give your feedback on this tool
Sign up for free to join and share with the community

0 user reviews

star_border star_border star_border star_border star_border
star star star star star

0 user reviews

star_border star_border star_border star_border star_border
star star star star star

No review has been posted.

LMAT forum

tutorial arrow
×
Communicate with other users
Participate in the forum to get support for using tools. Ask questions about technical specifications.
Take part in the discussion
Sign up for free to ask question and share your advices

No open topic.

LMAT classification

LMAT specifications

Unique identifier:
OMICS_02285
Software type:
Package/Module
Restrictions to use:
None
Programming languages:
C++, Python
Version:
1.2.6
Maintained:
Yes
Name:
Livermore Metagenomics Analysis Toolkit
Interface:
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
Computer skills:
Advanced
Stability:
Stable

LMAT distribution

versioning

tutorial arrow
×
Upload and version your source code
Get a DOI for each update to improve tool traceability. Archive your releases so the community can easily visualize progress on your work.
Facilitate your tool traceability
Sign up for free to upload your code and get a DOI

No versioning.

download

Credits

tutorial arrow
×
Promote your skills
Define all the tasks you managed and assign your profile the appropriate badges. Become an active member.
Promote your work
Sign up for free to badge your contributorship

Publications

Institution(s)

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).

By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.