DeepNGS navigator: exploring antibody NGS datasets using deep contrastive learning.

ABSTRACT:

Motivation

High-throughput sequencing uncovers how B-cells adapt in response to antigens by generating B-cell-receptor (BCR) sequences at an unprecedented scale. As BCR datasets grow to millions of sequences, using efficient computational methods becomes crucial. One important aspect of antibody sequence analysis is detecting clonal families or clusters of related sequences, whether they come from immunization, synthetic-libraries or even ML-generated datasets.

Results

We introduce deepNGS Navigator, a computational tool that leverages language models and contrastive learning to transform antibody sequences into intuitive 2D representations. The resulting 2D maps offer a visualization of overall diversity of input datasets, which can be clustered based on the sequence distan

SUBMITTER: MohammadiPeyhani H 

PROVIDER: S-EPMC12448221 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature