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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),
architecture-is-little-endian,
architecture-is-64-bit,
cmake,
libseqan3-dev (>= 3.4.0~rc.3),
libgtest-dev,
libxxhash-dev,
libcereal-dev,
libsimde-dev,
libyaml-cpp-dev,
pkgconf,
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: 4.7.0
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).
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