Metadata-Version: 1.0
Name: banner
Version: 0.0.2
Summary: banner is a tool for predicting microbiome labels based on hulk sketches
Home-page: http://will-rowe.github.io/
Author: Will Rowe
Author-email: will.rowe@stfc.ac.uk
License: MIT
Description: <div align="center">
            <img src="https://raw.githubusercontent.com/will-rowe/banner/master/misc/logo/banner-logo-with-text.png" alt="banner-logo" width="250">
            <hr>
            <a href="https://travis-ci.org/will-rowe/banner"><img src="https://travis-ci.org/will-rowe/banner.svg?branch=master" alt="travis"></a>
            <a href='http://hulk.readthedocs.io/en/latest/?badge=latest'><img src='https://readthedocs.org/projects/hulk/badge/?version=latest' alt='Documentation Status' /></a>
            <a href="https://github.com/will-rowe/banner/blob/master/LICENSE"><img src="https://img.shields.io/badge/license-MIT-orange.svg" alt="License"></a>
            <a href="https://zenodo.org/badge/latestdoi/144629592"><img src="https://zenodo.org/badge/144629592.svg" alt="DOI"></a>
        </div>
        
        ***
        
        ```
        BANNER is still under development - features and improvements are being added, so please check back soon.
        ```
        
        ***
        
        ## Overview
        
        `BANNER` is a tool that lives inside [HULK](https://github.com/will-rowe/hulk) and aims to make sense of **hulk sketches**. At the moment, it trains a [Random Forest Classifier](http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html) using a set of labelled **hulk sketches**. It can then use this model to predict the label of microbiomes as they are sketches by ``HULK``.
        
        For example, you could train `BANNER` using a set of microbiomes from patients that either have or haven't received antibiotic treatment. You can then use `BANNER` to predict whether a new microbiome sample exhibits signs of antibiotic dysbiosis. I will post more information and examples soon...
        
        ## Installation
        
        ### Bioconda
        
        ```
        conda install banner
        ```
        
        > note: if using Conda make sure you have added the [Bioconda](https://bioconda.github.io/) channel first
        
        #### Pip
        
        ```
        pip install banner
        ```
        
        ## Quick Start
        
        `BANNER` is called by typing **banner**, followed by the subcommand you wish to run. There are two main subcommands: **train** and **predict**. This quick start will show you how to get things running but it is recommended to follow the [HULK documentation](http://hulk-documentation.readthedocs.io/en/latest/?badge=latest).
        
        ```bash
        # Train a random forest classifier
        banner train -m hulk-banner-matrix.csv -o banner.rfc
        
        # Predict the label for a hulk sketch
        hulk sketch -f mystery-sample.fastq --stream -p 8 | banner predict -m banner.rfc
        ```
        
        
        ## Notes
        
        * only supports 2 labels at the moment
        
        * there is very limited checking and not many unit tests...
        
Platform: UNKNOWN
