Source: python-nanoget Section: science Priority: optional Maintainer: Debian Med Packaging Team Uploaders: Andreas Tille Build-Depends: debhelper-compat (= 13), dh-python, python3, python3-setuptools, python3-biopython, python3-nanomath, python3-pysam Standards-Version: 4.5.0 Vcs-Browser: https://salsa.debian.org/med-team/python-nanoget Vcs-Git: https://salsa.debian.org/med-team/python-nanoget.git Homepage: https://github.com/wdecoster/nanoget Rules-Requires-Root: no Package: python3-nanoget Architecture: all Section: python Depends: ${python3:Depends}, ${misc:Depends}, python3-biopython, python3-pysam, python3-nanomath Description: extract information from Oxford Nanopore sequencing data and alignments The Python3 module nanoget provides functions to extract useful metrics from Oxford Nanopore sequencing reads and alignments. . Data can be presented in the following formats, using the following functions: . * sorted bam file process_bam(bamfile, threads) * standard fastq file process_fastq_plain(fastqfile, 'threads') * fastq file with metadata from MinKNOW or Albacore process_fastq_rich(fastqfile) * sequencing_summary file generated by Albacore process_summary(sequencing_summary.txt, 'readtype') . Fastq files can be compressed using gzip, bzip2 or bgzip. The data is returned as a pandas DataFrame with standardized headernames for convenient extraction. The functions perform logging while being called and extracting data. Package: python3-nanoget-examples Architecture: all Section: python Depends: ${misc:Depends}, Enhances: python3-nanoget Description: example data for python3-nanoget (dealing with Oxford Nanopore data) The Python3 module nanoget provides functions to extract useful metrics from Oxford Nanopore sequencing reads and alignments. . Data can be presented in the following formats, using the following functions: . * sorted bam file process_bam(bamfile, threads) * standard fastq file process_fastq_plain(fastqfile, 'threads') * fastq file with metadata from MinKNOW or Albacore process_fastq_rich(fastqfile) * sequencing_summary file generated by Albacore process_summary(sequencing_summary.txt, 'readtype') . Fastq files can be compressed using gzip, bzip2 or bgzip. The data is returned as a pandas DataFrame with standardized headernames for convenient extraction. The functions perform logging while being called and extracting data. . This package just contains an example script and the data to run the example.