Source: seqan-raptor
Standards-Version: 4.7.4
Maintainer: Debian Med Packaging Team <debian-med-packaging@lists.alioth.debian.org>
Uploaders:
 Michael R. Crusoe <crusoe@debian.org>,
Section: science
Build-Depends:
 debhelper-compat (= 14),
 architecture-is-64-bit,
 architecture-is-little-endian,
 cmake,
 cppreference-doc-en-html <!nodoc>,
 doxygen <!nodoc>,
 ghostscript <!nodoc>,
 libcereal-dev,
 libgtest-dev,
 libseqan3-dev (>= 3.4.0~rc.3),
 libsimde-dev,
 libxxhash-dev,
 libyaml-cpp-dev,
 pkgconf,
 texlive-font-utils <!nodoc>,
 texlive-fonts-recommended <!nodoc>,
 texlive-latex-base <!nodoc>,
 texlive-latex-extra <!nodoc>,
 texlive-latex-recommended <!nodoc>,
 texlive-plain-generic <!nodoc>,
Vcs-Browser: https://salsa.debian.org/med-team/seqan-raptor
Vcs-Git: https://salsa.debian.org/med-team/seqan-raptor.git
Homepage: https://github.com/seqan/raptor

Package: seqan-raptor
Architecture: any
Depends:
 ${misc:Depends},
 ${shlibs:Depends},
Suggests:
 cwl-runner,
Description: pre-filter for querying very large collections of nucleotide sequences
 Raptor is a system for approximately searching many queries such as
 next-generation sequencing reads or transcripts in large collections of
 nucleotide sequences. Raptor uses winnowing minimizers to define a set of
 representative k-mers, an extension of the interleaved Bloom filters (IBFs) as
 a set membership data structure and probabilistic thresholding for minimizers.
 This approach allows compression and partitioning of the IBF to enable the
 effective use of secondary memory.

Package: seqan-raptor-doc
Architecture: all
Multi-Arch: foreign
Section: doc
Depends:
 ${misc:Depends},
Description: HTML & PDF documentation for seqan-raptor and its APIs
 Raptor is a system for approximately searching many queries such as
 next-generation sequencing reads or transcripts in large collections of
 nucleotide sequences. Raptor uses winnowing minimizers to define a set of
 representative k-mers, an extension of the interleaved Bloom filters (IBFs) as
 a set membership data structure and probabilistic thresholding for minimizers.
 This approach allows compression and partitioning of the IBF to enable the
 effective use of secondary memory.
 .
 This package contains Raptor's docs (HTML & PDF).
Build-Profiles: <!nodoc>