BreakNet

A deep learning method to detect deletion from long reads alignment. It is built with Tensorflow and Python 3.

Installation

Requirements

• python 3.7, numpy, scipy, pandas, Matplotlib, TensorFlow 2.4, pysam

1. Create a virtual environment

# create
conda create -n BreakNet python=3.6
# activate
conda activate BreakNet
# deactivate
conda deactivate

2. clone BreakNet

• After creating and activating the BreakNet virtual environment, download BreakNet from github:

git clone https://github.com/luojunwei/BreakNet.git
cd BreakNet

3. Install

conda activate BreakNet
conda install numpy, scipy, pandas, Matplotlib, TensorFlow, pysam

Tested data

The example data can be downloaded from

HG002

https://ftp.ncbi.nih.gov/giab/ftp/data/AshkenazimTrio/HG002_NA24385_son/PacBio_MtSinai_NIST/Baylor_NGMLR_bam_GRCh37/HG002_PB_70x_RG_HP10XtrioRTG.bam

HG00514

http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/hgsv_sv_discovery/working/20160905_smithm_pacbio_aligns/HG00514_bwamem_GRCh38DH_CHS_20160905_pacbio.bam

HG00733

http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/hgsv_sv_discovery/working/20160905_smithm_pacbio_aligns/HG00733_bwamem_GRCh38DH_PUR_20160905_pacbio.bam

NA19240

http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/hgsv_sv_discovery/working/20160905_smithm_pacbio_aligns/NA19240_bwamem_GRCh38DH_YRI_20160905_pacbio.bam

Usage

Train Model

1. Produce data for training

python breaknet.py data_mode bamfile_path output_data_folder vcf_path

  bamfile_path is the path of the alignment file about the reference and the long read set. And, the bam file should be sorted and indexed;

  output_data_folder is a folder which is used to store training data or evaluation data;

  vcf_path is the path of the vcf which is used to label training data;

2. Train a new model

python breaknet.py train_mode training_data_folder evaluation_data_folder trained_weight_path epochs

  First, we use commond 1 to produce training data, which is stored in the training_data_folder.
  
  Second, we use commond 1 to produce evaluation data, which is stored in the evaluation_data_folder.

  trained_weight_path is the path of the trained weight file of the model. Not include extension name.

  epochs are max training epochs.

Call deletion

In the folder "trained_weight", we give the trained weight files, which can directly used for calling deletions.

1. Produce data for call sv

python breaknet.py data_mode bamfile_path call_folder

2. Call deletion

python breaknet.py call_mode call_folder trained_weight_path bamfilepath