deepshm 0.0.1

A package for training and applying neural networks aimed to deal with genomic data

DeepSHM

This repository implements the model from "Deep learning model of somatic hypermutation reveals importance of sequence context beyond targeting of AID and Polη hotspots" by Tang, Krantsevich & MacCarthy. Using DeepSHM you can simply use one of the provided models to make SHM-related predictions for your data, or you can train your own CNN model for any task that uses DNA/RNA one-hot encoded data as input.

Instalation

If you want to play with the model

DeepSHM is on pypi, so it can be installed using pip:

pip install deepshm

If you are not familiar with python

You can also just download the deepshm_predict.zip archive and 0nce you extract it you can call the file deepshm_predict.py from the command line. Note that you still will need python installed as wells as several packages: tensorflow, numpy, scipy. deepshm_predict.py can be called in the following way:

python deepshm_predict.py input.fasta -o output.csv -k 15

where the input fasta file is the required input and the path to the output file and the length of k-mer (5, 9, 15 and 21) are optional. Default value for the output file is output.csv and default k is 15.