Simply download the executable from the latest release, via the following
wget https://github.com/GZHoffie/bbs/releases/download/v0.0.1/bbsAlternatively, build BBS from the source code. This tool is built with Seqan3. To properly build the package, you need to have GCC >= 11.3, G++ and CMake installed.
git clone https://github.com/GZHoffie/bbs.git
cd bbs
mkdir build
cd buildBuild the project with the command
cmake ../
cmake --build . --target bbs
This is going to download all the dependencies, and the executable is then available in build/bbs.
Currently, BBS supports input format that is similar to the CNR dataset. Below is a quick demo.
# Download the Microsoft CNR dataset
git clone https://github.com/microsoft/clustered-nanopore-reads-dataset.git
# Assume that we are still in the build/ directory
# To output the reconstructed sequence directly, use `./bbs -i <input_clusters> -l <read_length> -s <cluster_separator> > <output_file_name>`
./bbs -i clustered-nanopore-reads-dataset/Clusters.txt -l 110 -s "====" > output.txtThe separator is an indicator string that separates the clusters. If we read a line that contains the specified separator, we regard it as a new cluster.
For more detailed output, use the following command.
./bbs -i clustered-nanopore-reads-dataset/Clusters.txt -l 110 -s "====" -o output.csv > /dev/nullIn the output csv file, there will be 5 fields, indicating the index of the cluster, reconstructed sequence, the value of k used, the total path weight, and the confidence value.
read_id,reconstruction_result,k,path_weight,confidence
1,ACCATAATGCGTGGGGCCGACCTCGGAATGCGGTCTCCATGCGCGTTTCCTCCAACCTAAGGTAGCCTGTAGTTCATTGGACCTCTGATGGCGCTTATAGAAACCGGGAA,11,-14.9066,0.909951
2,TCGAAGCAGTAGGGCCTACCAAATAGGTTGGTCCTCCGTTGTATCTAAGGATTGAGTTTACCTGGCTTACACGGCAGGTACCGCCAATCTCGTCCGGCTCCGCGGCATCC,8,-32.2539,0.950223
3,AGTTAACGTCCCACGGCGAGGCACTCTTGATCCCCACCTTCAAGAGGTGTACCGGATCATGGAGAACAAGCATACGTCGCACGCACACCATTGGACGGCGAGTGCCGAGT,10,-44.4446,0.853414
Use the following for a detailed guide on other input parameters.
./bbs -h[1] Gu, Zhenhao, et al. "Efficient trace reconstruction in DNA storage systems using Bidirectional Beam Search." bioRxiv (2025): 2025-04.