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Source: python-dendropy
Maintainer: Debian Med Packaging Team <debian-med-packaging@lists.alioth.debian.org>
Uploaders: Andreas Tille <tille@debian.org>
Section: python
Testsuite: autopkgtest-pkg-python
Priority: optional
Build-Depends: debhelper-compat (= 13),
dh-python,
python3-all,
python3-setuptools
Standards-Version: 4.5.0
Vcs-Browser: https://salsa.debian.org/med-team/python-dendropy
Vcs-Git: https://salsa.debian.org/med-team/python-dendropy.git
Homepage: https://dendropy.org/
Rules-Requires-Root: no
Package: python3-dendropy
Architecture: all
Depends: ${shlibs:Depends},
${misc:Depends},
${python3:Depends}
Description: DendroPy Phylogenetic Computing Library (Python 3)
DendroPy is a Python library for phylogenetic computing. It provides
classes and functions for the simulation, processing, and manipulation
of phylogenetic trees and character matrices, and supports the reading
and writing of phylogenetic data in a range of formats, such as NEXUS,
NEWICK, NeXML, Phylip, FASTA, etc. Application scripts for performing
some useful phylogenetic operations, such as data conversion and tree
posterior distribution summarization, are also distributed and installed
as part of the library. DendroPy can thus function as a stand-alone
library for phylogenetics, a component of more complex multi-library
phyloinformatic pipelines, or as a scripting “glue” that assembles and
drives such pipelines.
.
This package provides python3 modules.
Package: sumtrees
Architecture: all
Depends: ${shlibs:Depends},
${misc:Depends},
${python3:Depends},
python3-dendropy
Description: Phylogenetic Tree Summarization and Annotation
SumTrees is a program to summarize non-parameteric bootstrap or
Bayesian posterior probability support for splits or clades on
phylogenetic trees.
.
The basis of the support assessment is typically given by a set of
non-parametric bootstrap replicate tree samples produced by programs
such as GARLI or RAxML, or by a set of MCMC tree samples produced by
programs such as Mr. Bayes or BEAST. The proportion of trees out of the
samples in which a particular split is found is taken to be the degree
of support for that split as indicated by the samples. The samples that
are the basis of the support can be distributed across multiple files,
and a burn-in option allows for an initial number of trees in each file
to be excluded from the analysis if they are not considered to be drawn
from the true support distribution.
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