Antibody sequences assembly method based on weighted de Bruijn graph.

de Bruijn graph de novo sequencing monoclonal antibody sequence alignment sequence assembly

Journal

Mathematical biosciences and engineering : MBE
ISSN: 1551-0018
Titre abrégé: Math Biosci Eng
Pays: United States
ID NLM: 101197794

Informations de publication

Date de publication:
31 01 2023
Historique:
medline: 11 5 2023
pubmed: 10 5 2023
entrez: 10 5 2023
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 37161102
doi: 10.3934/mbe.2023266
doi:

Substances chimiques

Antibodies 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

6174-6190

Auteurs

Yi Lu (Y)

Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China.

Cheng Ge (C)

Key Laboratory of Marine Drugs, Chinese Ministry of Education, School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, China.

Biao Cai (B)

Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China.

Qing Xu (Q)

Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China.

Ren Kong (R)

Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China.

Shan Chang (S)

Institute of Bioinformatics and Medical Engineering, School of Electrical and Information Engineering, Jiangsu University of Technology, Changzhou 213001, China.

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