deepgrp 0.2.1

DNA repeat annotations

DeepGRP is a python package used to predict genomic repetitive elements with a deep learning model consisting of bidirectional gated recurrent units with attention. The idea of DeepGRP was initially based on dna-nn, but was re-implemented and extended using TensorFlow 2.1. DeepGRP was tested for the prediction of HSAT2,3, alphoid, Alu and LINE-1 elements.

Getting Started

Installation

For installation you can use the PyPI version with:

pip install deepgrp

or install from this repository with:

git clone https://github.com/fhausmann/deepgrp
cd deepgrp
pip install .

Additionally you can install the developmental version with poetry:

git clone https://github.com/fhausmann/deepgrp
cd deepgrp
poetry install

Data preprocessing

For training and hyperparameter optimization the data have to be preprocessed. For inference / prediction the FASTA sequences can directly be used and you can skip this process. The provided script parse_rm can be used to extract repeat annotations from RepeatMasker annotations to a TAB seperated format by:

parse_rm GENOME.fa.out > GENOME.bed

The FASTA sequences have to be converted to a one-hot-encoded representation, which can be done with:

preprocess_sequence FASTAFILE.fa.gz

preprocess_sequence creates a one-hot-encoded representation in numpy compressed format in the same directory.

Hyperparameter optimization

For Hyperparameter optimization the github repository provides a jupyter notebook which can be used.

Hyperparameter optimization is based on the hyperopt package.

Training

Training of a model can be performed with the provided jupyter notebook.

Prediction

The prediction can be done with the deepgrp main function like:

deepgrp <modelfile> <fastafile> [<fastafile>, ...]

where <modelfile> contains the trained model in HDF5 format and <fastafile> is a (multi-)FASTA file containing DNA sequences. Several FASTA files can be given at once.

Requirements

Requirements are listed in pyproject.toml.

Additionally for compiling C/Cython code, a C compiler should be installed.

Further information

You can find material to reproduce the results in the repository deepgrp_reproducibility.