MetaPhlAn specifications


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



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  • person_outline Nicola Segata <>
  • person_outline Duy Tin Truong <>

Additional information

MetaPhlAn articles

MetaPhlAn citations

PMCID: 5310281

[…] preprocessing, in which tagcleaner, prinseq, deconseq and flash [22–25] were used to remove low quality reads and contamination from the human genome; (2) expanded phylogenetic analysis, in which metaphlan [26] was used to sensitively detect the presence of microbial species inoral samples; (3) refined phylogenetic analysis, in which grammy [27] was used to accurately estimate the relative […]

PMCID: 4938407

[…] genome sequence (wgs) reads. simulated communities of 20 million reads each were generated by random selection of wgs reads from 59 bacteria commonly found in the human gut microbiome (s1 table). metaphlan species abundances of the gut microbiomes of donors and patients in an fmt study (see below) were used to simulate realistic abundance profiles. sequence reads were drawn from among the 59 […]

PMCID: 4917526

[…] the high-resolution microbial tree of life with taxonomic annotations was obtained using standard parameters., shotgun reads were used to profile the composition of the microbial community using metaphlan version 1.7.7 (segata et al., 2012). the software was run with standard parameters but using—sensitive-local in the bowtie2 alignment step., moreover, two millions of the reads not aligned […]

PMCID: 3564958

[…] sequenced for metagenomics using the illumina gaiix platform1. 16s data processing and diversity estimates were performed using qiime27, and metagenomic data were taxonomically profiled using metaphlan13, metabolically profiled by humann26, and assembled for gene annotation and clustering into a unique catalog1. potential pathogens were identified using the patric database14, isolate […]

MetaPhlAn 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
MetaPhlAn 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.

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