Source: seqan-raptor
Section: science
Priority: optional
Maintainer: Debian Med Packaging Team <debian-med-packaging@lists.alioth.debian.org>
Uploaders: Michael R. Crusoe <crusoe@debian.org>
Build-Depends: debhelper-compat (= 13),
               cmake,
               libseqan3-dev (>= 3.3.0~rc.1),
               libgtest-dev,
               libxxhash-dev,
               libcereal-dev,
               libsimde-dev,
               libyaml-cpp-dev,
               pkg-config,
               doxygen <!nodoc>,
               cppreference-doc-en-html <!nodoc>,
               texlive-font-utils <!nodoc>,
               texlive-latex-base <!nodoc>,
               texlive-latex-recommended <!nodoc>,
               texlive-latex-extra <!nodoc>,
               texlive-plain-generic <!nodoc>,
               texlive-fonts-recommended <!nodoc>,
               ghostscript <!nodoc>
Standards-Version: 4.6.2
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
Rules-Requires-Root: no

Package: seqan-raptor
Architecture: any
Depends: ${shlibs:Depends}, ${misc: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
Depends: ${misc:Depends}
Section: doc
Build-Profiles: <!nodoc>
Multi-Arch: foreign
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).