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deepbinner (0.2.0-1) UNRELEASED; urgency=medium
* Initial release (Closes: #<bug>)
TODO:
1. python3-tensorflow (see
https://lists.debian.org/debian-science/2018/12/msg00023.html )
2. https://github.com/caseman/noise
3. mappy (https://github.com/lh3/minimap2/tree/master/python)
-> minimap2 is in new
-- Andreas Tille <tille@debian.org> Mon, 10 Dec 2018 13:34:46 +0100
Source: deepbinner
Maintainer: Debian Med Packaging Team <debian-med-packaging@lists.alioth.debian.org>
Uploaders: Andreas Tille <tille@debian.org>
Section: science
Priority: optional
Build-Depends: debhelper (>= 11~),
dh-python,
python3,
python3-setuptools,
python3-keras,
python3-h5py,
python3-numpy,
python3-edlib,
# python3-mappy,
# python3-noise,
# python3-tensorflow
Standards-Version: 4.2.1
Vcs-Browser: https://salsa.debian.org/med-team/deepbinner
Vcs-Git: https://salsa.debian.org/med-team/deepbinner.git
Homepage: https://github.com/rrwick/Deepbinner
Package: deepbinner
Architecture: any
Depends: ${shlibs:Depends},
${misc:Depends}
Description: demultiplexing barcoded Oxford Nanopore sequencing reads
Deepbinner is a tool for demultiplexing barcoded Oxford Nanopore
sequencing reads. It does this with a deep convolutional neural network
classifier, using many of the architectural advances that have proven
successful in image classification. Unlike other demultiplexers (e.g.
Albacore and Porechop), Deepbinner identifies barcodes from the raw
signal (a.k.a. squiggle) which gives it greater sensitivity and fewer
unclassified reads.
.
Reasons to use Deepbinner:
* To minimise the number of unclassified reads (use Deepbinner
by itself).
* To minimise the number of misclassified reads (use Deepbinner in
conjunction with Albacore demultiplexing).
* You plan on running signal-level downstream analyses, like
Nanopolish. Deepbinner can demultiplex the fast5 files which makes
this easier. Reasons to not use Deepbinner:
* You only have basecalled reads not the raw fast5 files (which
Deepbinner requires).
* You have a small/slow computer. Deepbinner is more computationally
intensive than Porechop.
* You used a sequencing/barcoding kit other than the ones Deepbinner
was trained on.
Format: https://www.debian.org/doc/packaging-manuals/copyright-format/1.0/
Upstream-Name: <pkg>
Source: <path_to_download>
Comment: **** Before manually editing this file you should give ****
scan-copyrights
**** available in cme + lib-config-model-dpkg-perl ****
**** package a try. For existing copyright files try ****
cme update dpkg-copyright
Files: *
Copyright: © 20xx-20yy <upstream>
License: <license>
Files: debian/*
Copyright: 2018 Andreas Tille <tille@debian.org>
License: <license>
#!/usr/bin/make -f
# DH_VERBOSE := 1
export LC_ALL=C.UTF-8
include /usr/share/dpkg/default.mk
# this provides:
# DEB_SOURCE: the source package name
# DEB_VERSION: the full version of the package (epoch + upstream vers. + revision)
# DEB_VERSION_EPOCH_UPSTREAM: the package's version without the Debian revision
# DEB_VERSION_UPSTREAM_REVISION: the package's version without the Debian epoch
# DEB_VERSION_UPSTREAM: the package's upstream version
# DEB_DISTRIBUTION: the distribution(s) listed in the current entry of debian/changelog
# SOURCE_DATE_EPOCH: the source release date as seconds since the epoch, as
# specified by <https://reproducible-builds.org/specs/source-date-epoch/>
# for hardening you might like to uncomment this:
# export DEB_BUILD_MAINT_OPTIONS=hardening=+all
%:
dh $@ --with python3 --buildsystem=pybuild
### When overriding auto_test make sure DEB_BUILD_OPTIONS will be respected
#override_dh_auto_test:
#ifeq (,$(filter nocheck,$(DEB_BUILD_OPTIONS)))
# do_stuff_for_testing
#endif
Reference:
Author: Ryan R Wick and Louise M Judd and Kathryn E Holt
Title: "Deepbinner: Demultiplexing barcoded Oxford Nanopore reads with deep convolutional neural networks"
Journal: bioRxiv
Year: 2018
Volume: 14
Number: 11
Pages: e1006583
DOI: 10.1101/366526
PMID: 30458005
URL: https://www.biorxiv.org/content/early/2018/07/10/366526
eprint: https://www.biorxiv.org/content/biorxiv/early/2018/07/10/366526.full.pdf
version=4
https://github.com/rrwick/Deepbinner/releases .*/archive/v?@ANY_VERSION@@ARCHIVE_EXT@