gtnet 0.0.1
A package for running Genome Taxonomy Network predictions
License: BSD-3-Clause
Requires Python: >=3.7
Keywords: python,microbiome,microbial-taxonomy,cross-platform,open-data,data-format,open-source,open-science,reproducible-research,machine-learning

GTNet
=====
The Genome Taxonomy Network for assigning microbial taxonomy to DNA sequences

## Getting started
Installing GTNet from PyPI
```bash
pip install gtnet
```

Installing GTNet from source
```bash
pip install git+https://github.com/exabiome/gtnet.git
```

## Running GTNet
Getting taxonomic classifications for all sequences in a Fasta file.
```bash
gtnet classify data/small.fna > data/small.tax.csv
```

### GTNet steps
GTNet consists of two main steps: 1) get scored predictions of taxonoimc assignments and 2) filter
scored predictions. The previous command combines these two commands into a single command with a 
default false-positive rate. The two steps have been separated into two commands for those who
want to experiment with different false-positive rates.

Getting predictions for all sequences in a Fasta file.
```bash
gtnet predict data/small.fna > data/small.tax.raw.csv
```
The first time you run `predict`, the model file will be downloaded and stored in the
same directory that the `gtnet` package is installed in. Therefore, for the this to be successful,
you must have write privileges on the directory that `gtnet` is installed in.

Filtering predictions 
```bash
gtnet filter --fpr 0.05 data/small.tax.raw.csv > data/small.tax.csv
```

LICENSE
=======

The Genome Taxonomy Network (GTNet) Copyright (c) 2022, The
Regents of the University of California, through Lawrence Berkeley
National Laboratory (subject to receipt of any required approvals
from the U.S. Dept. of Energy). All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

(1) Redistributions of source code must retain the above copyright notice,
this list of conditions and the following disclaimer.

(2) Redistributions in binary form must reproduce the above copyright
notice, this list of conditions and the following disclaimer in the
documentation and/or other materials provided with the distribution.

(3) Neither the name of the University of California, Lawrence Berkeley
National Laboratory, U.S. Dept. of Energy nor the names of its contributors
may be used to endorse or promote products derived from this software
without specific prior written permission.


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COPYRIGHT
=========

The Genome Taxonomy Network (GTNet) Copyright (c) 2022, The
Regents of the University of California, through Lawrence Berkeley
National Laboratory (subject to receipt of any required approvals
from the U.S. Dept. of Energy). All rights reserved.

If you have questions about your rights to use or distribute this software,
please contact Berkeley Lab's Intellectual Property Office at
IPO@lbl.gov.

NOTICE.  This Software was developed under funding from the U.S. Department
of Energy and the U.S. Government consequently retains certain rights.  As
such, the U.S. Government has been granted for itself and others acting on
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