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

MetaPhlAn | Metagenomic microbial community profiling using unique clade-specific marker genes

Estimates the relative abundance of microbial cells by mapping reads against a reduced set of clade-specific marker sequences. MetaPhlAn accurately profiles microbial communities and requires only minutes to process millions of metagenomic reads. This classifier compares each metagenomic read from a sample to this marker catalog to identify high-confidence matches. It finally compares metagenomic reads against this precomputed marker catalog using nucleotide BLAST searches in order to provide clade abundances for one or more sequenced metagenomes.

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.

MetaPhlAn 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.

MetaPhlAn classification

MetaPhlAn specifications

Unique identifier:
OMICS_02286
Alternative name:
MetaPhlAn2
Interface:
Command line interface
Input data:
Shotgun metagenome sequencing results.
Output data:
Table of microbial species and their relative abundance for each input.
Programming languages:
Python
Computer skills:
Advanced
Stability:
Stable
Maintained:
Yes
Name:
Metagenomic Phylogenetic Analysis
Software type:
Package/Module
Restrictions to use:
None
Input format:
FASTQ, SAM
Operating system:
Unix/Linux
License:
MIT License
Version:
2
Requirements:
Python, Bowtie, Numpy, Pandas, BioPython, SciPy, Matplotlib, biom

MetaPhlAn 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

MetaPhlAn support

Documentation

Maintainers

  • Nicola Segata <>
  • Duy Tin Truong <>

Additional information

http://huttenhower.sph.harvard.edu/metaphlan

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)

Centre for Integrative Biology, University of Trento, Trento, Italy; Biostatistics Department, Harvard School of Public Health, Boston, MA, USA; The Broad Institute of MIT and Harvard, Cambridge, MA, USA

Funding source(s)

Supported in part by the US National Institutes of Health (grants R01HG005969 and U54DE023798), the US National Science Foundation (grant DBI-1053486), the US Army Research Office (grant W911NF-11-1-0473), Danone Research (grant PLF-5972-GD) the European Union Seventh Framework Programme (Marie Curie grant PCIG13-618833), the Italian Ministry of Education, University and Research (grant FIR RBFR13EWWI), Fondazione Caritro (grant Rif.Int.2013.0239) and Terme di Comano.

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