Source: shasta Maintainer: Debian Med Packaging Team Uploaders: Shayan Doust Section: science Priority: optional Build-Depends: debhelper-compat (= 13), dh-python, dh-exec, cmake, patchelf, chrpath, libboost-all-dev, libpng-dev, ncbi-blast+, python3-sphinx, python3-dev, libseqan2-dev, libspoa-dev, python3-pybind11, libcpu-features-dev [any-amd64], libcereal-dev, libblas-dev, liblapack-dev, gfortran Standards-Version: 4.6.1 Vcs-Browser: https://salsa.debian.org/med-team/shasta Vcs-Git: https://salsa.debian.org/med-team/shasta.git Homepage: https://github.com/chanzuckerberg/shasta Rules-Requires-Root: no Package: shasta Architecture: any-amd64 arm64 # even if one comments out the sections that forbid compilation on other archs # one gets this error message: # undefined reference to `__sync_bool_compare_and_swap_16' # see src/dset64.hpp for more details Depends: ${misc:Depends}, ${shlibs:Depends}, python3-shasta (= ${binary:Version}), Description: nanopore whole genome assembly (binaries and scripts) De novo assembly from Oxford Nanopore reads. The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by Oxford Nanopore flow cells. . Computational methods used by the Shasta assembler include: . * Using a run-length representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads. . * Using in some phases of the computation a representation of the read sequence based on markers, a fixed subset of short k-mers (k ≈ 10). . Shasta assembly quality is comparable or better than assembly quality achieved by other long read assemblers. . This package contains the executable binaries (tools) and accommodating scripts. Package: python3-shasta Architecture: any-amd64 arm64 Section: python Depends: ${python3:Depends}, ${shlibs:Depends}, ${misc:Depends}, ncbi-blast+ Description: nanopore whole genome assembly (dynamic library) De novo assembly from Oxford Nanopore reads. The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by Oxford Nanopore flow cells. . Computational methods used by the Shasta assembler include: . * Using a run-length representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads. . * Using in some phases of the computation a representation of the read sequence based on markers, a fixed subset of short k-mers (k ≈ 10). . Shasta assembly quality is comparable or better than assembly quality achieved by other long read assemblers. . This package contains the dynamic library that can be interfaced and imported within Python. Package: python3-shasta-doc Architecture: all Multi-Arch: foreign Section: doc Built-Using: ${sphinxdoc:Built-Using} Depends: ${sphinxdoc:Depends}, ${misc:Depends} Recommends: shasta, python3-shasta Description: nanopore whole genome assembly (documentation) De novo assembly from Oxford Nanopore reads. The goal of the Shasta long read assembler is to rapidly produce accurate assembled sequence using as input DNA reads generated by Oxford Nanopore flow cells. . Computational methods used by the Shasta assembler include: . * Using a run-length representation of the read sequence. This makes the assembly process more resilient to errors in homopolymer repeat counts, which are the most common type of errors in Oxford Nanopore reads. . * Using in some phases of the computation a representation of the read sequence based on markers, a fixed subset of short k-mers (k ≈ 10). . Shasta assembly quality is comparable or better than assembly quality achieved by other long read assemblers. . This package contains the documentation for the shasta and python3-shasta packages.