AtacWorks Release 0.1.0

This is the first official release of AtacWorks. AtacWorks is a deep learning-based toolkit for denoising and peak calling from noisy ATAC-Seq data. While currently tested only on ATAC-Seq, AtacWorks can also be applied to other epigenomic data types such as ChIP-Seq or DNase-Seq. A detailed description and results for several use cases are given in the preprint: https://www.biorxiv.org/content/10.1101/829481

The main components of this release are:

1. Data reading and writing from BED, BEDGRAPH and BigWig formats
2. Training deep learning models using a customizable resnet architecture
3. Pre-trained models that can be applied to new data
4. Inference using a newly trained or provided model, producing a denoised ATAC-Seq signal and peak calls
5. Evaluating model performance on denoising and peak calling tasks.