Antibody sequences assembly method based on weighted de Bruijn graph
peer-reviewed · Mathematical Biosciences and Engineering · 2023
| Date | 2023-02-02 |
| Type | peer-reviewed |
| Venue | Mathematical Biosciences and Engineering |
| Publisher | American Institute of Mathematical Sciences (AIMS) |
| Contribution | post-processor |
| DOI | 10.3934/mbe.2023266 |
| Citations (OpenAlex) | 0 |
Abstract
With the development of next-generation protein sequencing technologies, sequence assembly algorithm has become a key technology for de novo sequencing process. At present, the existing methods can address the assembly of an unknown single protein chain. However, for monoclonal antibodies with light and heavy chains, the assembly is still an unsolved question. To address this problem, we propose a new assembly method, DBAS, which integrates the quality scores and sequence alignment scores from de novo sequencing peptides into a weighted de Bruijn graph to assemble the final protein sequences. The established method is used to assembling sequences from two datasets with mixed light and heavy chains from antibodies. The results show that the DBAS can assemble long antibody sequences for both mixed light and heavy chains and single chains. In addition, DBAS is able to distinguish the light and heavy chains by using BLAST sequence alignment. The results show that the algorithm has good performance for both target sequence coverage and contig assembly accuracy.
Methods and tools
- DBAS: Assembles de novo peptide reads into antibody light and heavy chains using a de Bruijn graph weighted by de novo quality and alignment scores.
Methods it uses
- PEAKS: Commercial DP-based de novo