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        "author": "Wouter De Coster",
        "author_email": "decosterwouter@gmail.com",
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        "classifiers": [
            "Development Status :: 4 - Beta",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Topic :: Scientific/Engineering :: Bio-Informatics"
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        "description": "# NanoStat\n\nCalculate various statistics from a long read sequencing dataset in fastq, bam or albacore sequencing summary format.\n\n[![Twitter URL](https://img.shields.io/twitter/url/https/twitter.com/wouter_decoster.svg?style=social&label=Follow%20%40wouter_decoster)](https://twitter.com/wouter_decoster)\n[![install with conda](https://anaconda.org/bioconda/nanostat/badges/installer/conda.svg)](https://anaconda.org/bioconda/nanostat)\n[![Build Status](https://travis-ci.org/wdecoster/nanostat.svg?branch=master)](https://travis-ci.org/wdecoster/nanostat)\n\n\n\n### INSTALLATION\n\nNanoStat is written for Python3 and will not work in Python2.7 or older.\n\n`pip install nanostat`  \nor  \n`conda install -c bioconda nanostat`\n\n\n### USAGE\n```\nNanoStat [-h] [-v] [-o OUTDIR] [-p PREFIX] [-n NAME] [-t N]\n                [--barcoded] [--readtype {1D,2D,1D2}]\n                (--fastq file [file ...] | --fasta file [file ...] | --summary file [file ...] | --bam file [file ...])\n\nCalculate statistics of long read sequencing dataset.\n\nGeneral options:\n  -h, --help            show the help and exit\n  -v, --version         Print version and exit.\n  -o, --outdir OUTDIR   Specify directory in which output has to be created.\n  -p, --prefix PREFIX   Specify an optional prefix to be used for the output file.\n  -n, --name NAME       Specify a filename/path for the output, stdout is the default.\n  -t, --threads N       Set the allowed number of threads to be used by the script.\n\nInput options.:\n  --barcoded            Use if you want to split the summary file by barcode\n  --readtype {1D,2D,1D2}\n                        Which read type to extract information about from summary. Options are 1D, 2D,\n                        1D2\n\nInput data sources, one of these is required.:\n  --fastq file [file ...]\n                        Data is in one or more (compressed) fastq file(s).\n  --fasta file [file ...]\n                        Data is in one or more (compressed) fasta file(s).\n  --summary file [file ...]\n                        Data is in one or more (compressed) summary file(s)generated by albacore.\n  --bam file [file ...]\n                        Data is in one or more sorted bam file(s).\n\nEXAMPLES:\n  NanoStat --fastq reads.fastq.gz --outdir statreports\n  NanoStat --summary sequencing_summary1.txt sequencing_summary2.txtsequencing_summary3.txt --readtype 1D2\n  NanoStat --bam alignment.bam alignment2.bam\n```\n\n#### EXAMPLES\n```\nNanoStat --fastq reads.fastq.gz --outdir statreports\nNanoStat --summary sequencing_summary1.txt sequencing_summary2.txt sequencing_summary3.txt --readtype 1D2\nNanoStat --bam alignment.bam alignment2.bam\n```\n\n### Example output\n```\nGeneral summary:\t \nActive channels:\t502\nMean read length:\t8593.5\nMean read quality:\t10.8\nMedian read length:\t5168.0\nMedian read quality:\t11.2\nNumber of reads:\t408254\nRead length N50:\t15141\nTotal bases:\t3508315665\nNumber, percentage and megabases of reads above quality cutoffs\n>Q5:\t406428 (99.6%) 3502.0Mb\n>Q7:\t395016 (96.8%) 3234.5Mb\n>Q10:\t305509 (74.8%) 2475.9Mb\n>Q12:\t87903 (21.5%) 422.9Mb\n>Q15:\t124 (0.0%) 0.1Mb\nTop 5 highest mean basecall quality scores and their read lengths\n1:\t16.2 (407; a803bcfc-9d7a-4a87-84e4-1a0296113700)\n2:\t16.2 (880; f5fee32a-9471-4a68-8697-a71887599757)\n3:\t16.1 (729; 3ea23a79-641e-41ab-bb5b-c22609977136)\n4:\t16.1 (1057; b0cef5fd-c5e1-4539-9591-b7376b2953e8)\n5:\t15.8 (841; 3d4f8075-6151-4147-bdc3-e5d53ff66084)\nTop 5 longest reads and their mean basecall quality score\n1:\t255821 (6.8; 7d069f04-d4db-4f12-a1b9-c19d70993492)\n2:\t254573 (7.1; a245999b-de28-4720-a8c3-0d5cbb26e473)\n3:\t253711 (7.0; a84b106b-13d3-4bfa-b548-71a47c9032c3)\n4:\t245784 (7.0; 2a60ee11-8793-46c1-a3d9-667bc4e70405)\n5:\t245776 (7.1; 72a8cf33-75fd-4c07-8a4c-7516b690938b)\n```\n\nI welcome all suggestions, bug reports, feature requests and contributions. Please leave an [issue](https://github.com/wdecoster/nanostat/issues) or open a pull request. I will usually respond within a day, or rarely within a few days.\n\n\n## CITATION\nIf you use this tool, please consider citing our [publication](https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/bty149/4934939).",
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