Source: libslow5lib Maintainer: Debian Med Packaging Team Uploaders: Andreas Tille Section: science Priority: optional Build-Depends: debhelper-compat (= 13), cmake, d-shlibs, dh-python, python3-all-dev, libstreamvbyte-dev, libzstd-dev, zlib1g-dev, cython3, python3-setuptools, python3-numpy, python3-wheel Standards-Version: 4.6.2 Vcs-Browser: https://salsa.debian.org/med-team/libslow5lib Vcs-Git: https://salsa.debian.org/med-team/libslow5lib.git Homepage: https://github.com/hasindu2008/slow5lib Rules-Requires-Root: no Package: libslow5-0 Architecture: any Section: libs Depends: ${shlibs:Depends}, ${misc:Depends} Multi-Arch: same Description: library for reading & writing SLOW5 files Slow5lib is a software library for reading & writing SLOW5 files. Slow5lib is designed to facilitate use of data in SLOW5 format by third- party software packages. Existing packages that read/write data in FAST5 format can be easily modified to support SLOW5. . SLOW5 is a new file format for storing signal data from Oxford Nanopore Technologies (ONT) devices. SLOW5 was developed to overcome inherent limitations in the standard FAST5 signal data format that prevent efficient, scalable analysis and cause many headaches for developers. SLOW5 can be encoded in human-readable ASCII format, or a more compact and efficient binary format (BLOW5) - this is analogous to the seminal SAM/BAM format for storing DNA sequence alignments. The BLOW5 binary format supports *zlib* (DEFLATE) compression, or other compression methods, thereby minimising the data storage footprint while still permitting efficient parallel access. Detailed benchmarking experiments have shown that SLOW5 format is an order of magnitude faster and significantly smaller than FAST5. Package: libslow5-dev Architecture: any Section: libdevel Depends: libslow5-0 (= ${binary:Version}), ${shlibs:Depends}, ${misc:Depends} Multi-Arch: same Description: header and static library for reading & writing SLOW5 files Slow5lib is a software library for reading & writing SLOW5 files. Slow5lib is designed to facilitate use of data in SLOW5 format by third- party software packages. Existing packages that read/write data in FAST5 format can be easily modified to support SLOW5. . SLOW5 is a new file format for storing signal data from Oxford Nanopore Technologies (ONT) devices. SLOW5 was developed to overcome inherent limitations in the standard FAST5 signal data format that prevent efficient, scalable analysis and cause many headaches for developers. SLOW5 can be encoded in human-readable ASCII format, or a more compact and efficient binary format (BLOW5) - this is analogous to the seminal SAM/BAM format for storing DNA sequence alignments. The BLOW5 binary format supports *zlib* (DEFLATE) compression, or other compression methods, thereby minimising the data storage footprint while still permitting efficient parallel access. Detailed benchmarking experiments have shown that SLOW5 format is an order of magnitude faster and significantly smaller than FAST5. . This is the development package containing headers and static library. Package: python3-slow5 Architecture: any Section: python Depends: libslow5-0 (= ${binary:Version}), ${shlibs:Depends}, ${python3:Depends}, ${misc:Depends} Description: Python3 modul for reading & writing SLOW5 files Slow5lib is a software library for reading & writing SLOW5 files. Slow5lib is designed to facilitate use of data in SLOW5 format by third- party software packages. Existing packages that read/write data in FAST5 format can be easily modified to support SLOW5. . SLOW5 is a new file format for storing signal data from Oxford Nanopore Technologies (ONT) devices. SLOW5 was developed to overcome inherent limitations in the standard FAST5 signal data format that prevent efficient, scalable analysis and cause many headaches for developers. SLOW5 can be encoded in human-readable ASCII format, or a more compact and efficient binary format (BLOW5) - this is analogous to the seminal SAM/BAM format for storing DNA sequence alignments. The BLOW5 binary format supports *zlib* (DEFLATE) compression, or other compression methods, thereby minimising the data storage footprint while still permitting efficient parallel access. Detailed benchmarking experiments have shown that SLOW5 format is an order of magnitude faster and significantly smaller than FAST5. . This is the Python3 module.