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Add documentation for bins and sequences (#41)
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docs/source/usage.rst

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@@ -5,7 +5,28 @@ GTNet comes with multiple commands. The simplest way of running GTNet is to use
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.. code:: bash
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gtnet classify data/small.fna > data/small.tax.csv
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gtnet classify genome.fna > genome.tax.csv
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This command generates one classification for the entire file, and should be used to get classification for metagenome bin.
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Use the ``-s/--seqs`` flag to get classifications for the individual sequences in ``genome.fna``
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.. Attention::
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The first time you run ``classify`` and ``predict`` (see below), the model file will be downloaded and stored in the same
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directory that the *gtnet* package is installed in. Therefore, for the this to be successful, you must have write privileges
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on the directory that *gtnet* is installed in.
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.. code:: bash
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gtnet classify --seqs genome.fna > genome.seqs.tax.csv
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The ``classify`` command can take multiple fasta files, and will produce line per file in the output. For example, the following
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command will contain two lines:
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.. code:: bash
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gtnet classify bin1.fna bin2.fna > bins.tax.csv
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GTNet steps
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Getting predictions
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^^^^^^^^^^^^^^^^^^^
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To get predictinos for all sequences in a Fasta file, use the ``predict`` subcommand.
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To get predictinos for all sequences in a Fasta file, use the ``predict`` subcommand. This command also accepts multiple fasta files
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and the ``-s/--seqs`` argument for getting predictions for individual sequences.
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.. code:: bash
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gtnet predict data/small.fna > data/small.tax.raw.csv
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The first time you run ``predict``, the model file will be downloaded and stored in the
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same directory that the *gtnet* package is installed in. Therefore, for the this to be successful,
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you must have write privileges on the directory that *gtnet* is installed in.
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gtnet predict genome.fna > genome.tax.raw.csv
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Filtering predictions
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^^^^^^^^^^^^^^^^^^^^^
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.. code:: bash
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gtnet filter --fpr 0.05 data/small.tax.raw.csv > data/small.tax.csv
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gtnet filter --fpr 0.05 genome.tax.raw.csv > genome.tax.csv
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The ``filter`` command supports predictions for whole files and individual sequences.
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GPU acceleration
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----------------

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