Installation
March 7, 2026 ยท View on GitHub
[BMC Bioinformatics'23] cnnLSV: detecting structural variants by encoding long-read alignment information and convolutional neural network
Installation
Clone
git clone https://github.com/mhuidong/cnnLSV.git
Dependencies
python3, cv2, numpy, torch, torchvision, pysam, cigar
Usage
Detecting SVs
python cnnLSV.py <sorted.bam> <initial.vcf> <filtered.vcf> --dataset <real/sim> --model <simmodel.pt/realmodel.pt>
[OPTIONAL] Removing Redundant information
CnnLSV outputs the callset merged of several callers. This means that one SV may be detected by several callers. You can use the foolowing command to obtain unique result.
python cnnLSV_rmrd.py <multi.vcf> <unique.vcf>
Datasets
HG00512, HG00513, HG00514, HG00731, HG00732, HG00733, NA19238, NA19239 and NA19240 datasets can be downloaded from:
http://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/hgsv_sv_discovery/working/20160905_smithm_pacbio_aligns/
HG002 CLR and HG002 CCS datasets can be downloaded from:
https://ftp.ncbi.nih.gov/giab/ftp/data/AshkenazimTrio/
Contact
Email: mahd@nbjl.nankai.edu.cn