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        "author": "Mike Trizna",
        "author_email": "triznam@si.edu",
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        "description": "# assembly_stats\n\nA Python library that takes a FASTA file as input and calculates both scaffold and contig statistics (N50, L50, etc.) from a scaffold FASTA file. It does this by breaking each scaffold wherever there is more than one N and then calculating statistics for both the scaffolds and contigs.\n\nThis is a re-write of [fasta_metadata_parser](https://github.com/pbfrandsen/fasta_metadata_parser) to speed up the old implementation, and -- most importantly -- to learn how to install Python scripts onto the Smithsonian HPC.\n\n## Installation\n\n```\npip install assembly_stats\n```\n\n## Usage\n\n```\n  $ assembly_stats -h\n\n    usage: assembly_stats [-h] filename\n\n    Calculate statistics about genome assemblies.\n\n    positional arguments:\n      filename    Genome file in FASTA format.\n\n    optional arguments:\n      -h, --help  show this help message and exit\n```\n\nAfter calculating the statistics for the genome assembly, they will be printed out in JSON format.\n\nNext steps\n----------\n\n* Add ability to save NumPy sequence length arrays for further visualization, since generating these are what takes the most time.\n\n\n",
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