Metadata-Version: 2.1
Name: alfie
Version: 1.0
Summary: alignment free identification of edna
Home-page: https://github.com/CNuge/alfie
Author: Cam Nugent
Author-email: nugentc@uoguelph.ca
License: LICENSE.md
Platform: UNKNOWN
Requires-Python: >=3.6
Requires-Dist: numpy (>=1.18.1)
Requires-Dist: tensorflow (>=2.0.0)
Requires-Dist: scikit-learn (>=0.21.3)
Requires-Dist: pandas (>=0.25.1)


alfie: an alignment-free, kingdom level taxonomic classifier for DNA barcode data. 

Alfie classifies sequences using a neural network which takes k-mer frequencies (default k = 4)
as inputs and makes kingdom level classification predictions. At present, the program contains 
trained models for classification of cytochrome c oxidase I (COI) barcode sequences to the 
taxonomic level: kingdom. The program is effective at classifying sequences >200 base pairs in 
length, and no alignment information is needed.

Alfie can be deployed from the command line for rapid file-to-file classification of sequences. 
This is an effective means of separating contaminant sequences in a DNA metabarcoding or 
environmental DNA dataset from sequences of interest.

For increased control, alfie can also be deployed as a module from within Python. The alfie 
package also contains functions that can aid a user in the training and application of a custom 
alignment-free classifier, which allows the program to be applied to different DNA barcodes 
(or genes) or on different taxonomic levels.