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"info": {
"author": "Michal Hozza",
"author_email": "mhozza@gmail.com",
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"Development Status :: 2 - Pre-Alpha",
"Intended Audience :: Science/Research",
"License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
"Natural Language :: English",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.4",
"Programming Language :: Python :: 3.5",
"Topic :: Scientific/Engineering :: Bio-Informatics"
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"description": "CovEst\n======\n\nTool that estimates coverage (and genome size) of dna sequence from\nreads.\n\n.. image:: https://badge.fury.io/py/covest.svg\n :target: https://badge.fury.io/py/covest\n.. image:: https://travis-ci.org/mhozza/covest.svg?branch=master\n :target: https://travis-ci.org/mhozza/covest\n\nRequirements\n------------\n- python 3.4+\n- python3-dev\n- gcc\n\nInstallation\n------------\nWe suggest to install *CovEst* in python3 virtual environment.\n\n``pip install covest``\n\nFor development:\n~~~~~~~~~~~~~~~~\n\n``pip install -e .`` from the project directory\n\nUsage\n-----\n\ntype ``covest --help`` for the usage.\n\nBasic Usage:\n~~~~~~~~~~~~\n``covest histogram -m model -k K -r read_length``\n\n- You can specify the read file using ``-s reads.fa`` parameter for more precise genome size computation.\n- default *K* is 21\n- default *read length* is 100\n- currently, the supported models are:\n\n - basic: for simple genomes without repeats\n - repeat: for genomes with repetitive sequences\n\nInput Histogram Specification:\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\nThe input histogram can be generated from the read data using `jellyfish `__.\n\n- ``jellyfish count -m K -C reads.fa -o table.jf``\n- ``jellyfish histo table.jf -o reads.hist``\n\nThe format of the histogram is just list of lines. Each lines contains an index and value separated by space.\n\nOutput Specification:\n~~~~~~~~~~~~~~~~~~~~~\nCovEst outputs it's results in simple subset of YAML format for best human readability and possibility of machine processing.\n\nThe output are lines containing ``key: value``. The most important keys are ``coverage`` and ``genome_size`` (or ``genome_size_reads`` if reads size was specified).\n\nOther included tools\n--------------------\n\n- ``geset.py`` tool for estimation genome size from reads size and known\n coverage\n- ``reads_size.py`` tool for computation of the total reads size\n- ``kmer_hist.py`` custom khmer histogram computation, it is much slower than other tools, so use it only if you have no other option.\n- ``read_sampler.py`` script for subsampling reads, useful if you have very high coverage data and want to make it smaller.\n- ``fasta_length.py`` get total length of all sequences in fasta file.\n\nCopyright and citation\n----------------------\n\nCovEst is licenced under `GNU GPLv3 `__ license.\n\nCovEst is research software, so you should cite us when you use it in scientific publications!\n Hozza, M., Vina\u0159, T., & Brejov\u00e1, B. (2015, September). How Big is that Genome? Estimating Genome Size and Coverage from k-mer Abundance Spectra. In String Processing and Information Retrieval (pp. 199-209). Springer International Publishing.",
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