Source: qiime
Section: contrib/science
Priority: extra
Maintainer: Debian Med Packaging Team <debian-med-packaging@lists.alioth.debian.org>
Uploaders: Steffen Moeller <moeller@debian.org>, Tim Booth <tbooth@ceh.ac.uk>
Build-Depends: debhelper (>= 8), python, python-central, python-cogent, python-numpy, python-matplotlib
Standards-Version: 3.9.2
Homepage: http://qiime.sourceforge.net/
Vcs-Browser: http://svn.debian.org/wsvn/debian-med/trunk/packages/qiime/trunk/?rev=0&sc=0
Vcs-Svn: svn://svn.debian.org/svn/debian-med/trunk/packages/qiime/trunk/
XS-Python-Version: >= 2.5

Package: qiime
Architecture: all
Depends: ${shlibs:Depends}, ${misc:Depends}, ${misc:Depends}, ${python:Depends}, python-pynast, python-cogent ( >= 1.5 )
Recommends: blast2, cd-hit, denoiser, rdp-classifier, chimeraslayer, muscle, infernal, fasttree
Suggests: t-coffee, cytoscape
Conflicts: bio-linux-qiime
XB-Python-Version:  ${python:Versions}
Description: Quantitative Insights Into Microbial Ecology
 QIIME (canonically pronounced ‘Chime’) is a pipeline for performing
 microbial community analysis that integrates many third party tools which
 have become standard in the field. A standard QIIME analysis begins with
 sequence data from one or more sequencing platforms, including Sanger,
 Roche/454, and Illumina GAIIx. With all the underlying tools installed,
 of which not all are yet available in Debian (or any other Linux
 distribution), QIIME can perform library de-multiplexing and quality
 filtering; denoising with PyroNoise; OTU and representative set picking
 with uclust, cdhit, mothur, BLAST, or other tools; taxonomy assignment
 with BLAST or the RDP classifier; sequence alignment with PyNAST, muscle,
 infernal, or other tools; phylogeny reconstruction with FastTree, raxml,
 clearcut, or other tools; alpha diversity and rarefaction, including
 visualization of results, using over 20 metrics including Phylogenetic
 Diversity, chao1, and observed species; beta diversity and rarefaction,
 including visualization of results, using over 25 metrics including
 weighted and unweighted UniFrac, Euclidean distance, and Bray-Curtis;
 summarization and visualization of taxonomic composition of samples
 using pie charts and histograms; and many other features.
 .
 QIIME includes parallelization capabilities for many of the
 computationally intensive steps. By default, these are configured to
 utilize a mutli-core environment, and are easily configured to run in
 a cluster environment. QIIME is built in Python using the open-source
 PyCogent toolkit. It makes extensive use of unit tests, and is highly
 modular to facilitate custom analyses.
