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CFIA OLC Genome Quality Assessment with Machine Learning

Project description

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# GenomeQAML: Genome Quality Assesment with Machine Learning

The GenomeQAML is a script that uses a pre-computed ExtraTreesClassifier model in order to
classify FASTA-formatted _de novo_ assemblies as bad, good, or very good. It's easy to use,
and has minimal dependencies.

## External Dependencies

- [Mash (v2.0 or greater)](
- [Prodigal (>=2.6.2)](

Both of these need to be downloaded and included on your $PATH.

## Installation

All you need to do is install with pip: `pip install genomeqaml`.

Usage of a virtualenv
is highly recommended.

## Usage

GenomeQAML takes a directory containing uncompressed fasta files as input - these will be classified and a
report written to a CSV-formatted file for your inspection.

To run, type ` -t /path/to/fasta/folder`

This will create a report, by default called `QAMLreport.csv`. You can change the name
of the report with the `-r` argument.

usage: [-h] -t TEST_FOLDER [-r REPORT_FILE]

optional arguments:
-h, --help show this help message and exit
-t TEST_FOLDER, --test_folder TEST_FOLDER
Path to folder containing FASTA files you want to
-r REPORT_FILE, --report_file REPORT_FILE
Name of output file. Default is QAMLreport.csv.


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Filename, size & hash SHA256 hash help File type Python version Upload date
GenomeQAML-0.0.11.tar.gz (8.1 MB) Copy SHA256 hash SHA256 Source None Feb 5, 2018

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