metaphlan2 2.7.5-1 source package in Ubuntu


metaphlan2 (2.7.5-1) unstable; urgency=medium

  * New upstream version (no data shiped with this archive any more)
  * Standards-Version: 4.1.3
  * debhelper 11
  * db_v20/mpa_v20_m200.pkl was removed from upstream source so we can not
    install this file

 -- Andreas Tille <email address hidden>  Fri, 16 Feb 2018 11:12:16 +0100

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Uploaded by:
Debian Med on 2018-02-16
Uploaded to:
Original maintainer:
Debian Med
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Bionic release on 2018-02-16 universe misc


Bionic: [FULLYBUILT] amd64


File Size SHA-256 Checksum
metaphlan2_2.7.5-1.dsc 2.0 KiB 059308e82c89967faa71248ff2bf5187ab03a59f8aa46aab522a5a1f12e5ec45
metaphlan2_2.7.5.orig.tar.bz2 160.4 KiB c114392a70307f5896a60b6b48126b0fc18873b590fc1dfeba4bbbbfbcb33ee8
metaphlan2_2.7.5-1.debian.tar.xz 11.3 KiB 022705b90259b2e301e80bdfaee9592a78f8784c8d4895f2d714c3f30b3ca917

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Binary packages built by this source

metaphlan2: Metagenomic Phylogenetic Analysis

 MetaPhlAn is a computational tool for profiling the composition of
 microbial communities (Bacteria, Archaea, Eukaryotes and Viruses) from
 metagenomic shotgun sequencing data with species level resolution. From
 version 2.0, MetaPhlAn is also able to identify specific strains (in the
 not-so-frequent cases in which the sample contains a previously
 sequenced strains) and to track strains across samples for all species.
 MetaPhlAn 2.0 relies on ~1M unique clade-specific marker genes (the
 marker information file can be found at
 usr/share/metaphlan2/utils/markers_info.txt.bz2) identified from
 ~17,000 reference genomes (~13,500 bacterial and archaeal, ~3,500 viral,
 and ~110 eukaryotic), allowing:
  * unambiguous taxonomic assignments;
  * accurate estimation of organismal relative abundance;
  * species-level resolution for bacteria, archaea, eukaryotes and
  * strain identification and tracking
  * orders of magnitude speedups compared to existing methods.
  * metagenomic strain-level population genomics