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An unbiased comparison of immunoglobulin sequence aligners. | LitMetric

An unbiased comparison of immunoglobulin sequence aligners.

Brief Bioinform

Faculty of Engineering, Bar Ilan University, 5290002 Ramat Gan, Israel.

Published: September 2024

AI Article Synopsis

  • Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is essential for studying the adaptive immune system, but analyzing the data requires accurate immunoglobulin (Ig) sequence alignments.
  • Currently, there's no standardized method for comparing different Ig sequence aligners, making it difficult to know which is best for specific tasks.
  • The introduction of GenAIRR, a simulation framework, allows for realistic modeling of Ig sequences and their complexities, providing a way to fairly evaluate various alignment tools and improve our understanding of adaptive immunity.

Article Abstract

Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is critical for our understanding of the adaptive immune system's dynamics in health and disease. Reliable analysis of AIRR-seq data depends on accurate rearranged immunoglobulin (Ig) sequence alignment. Various Ig sequence aligners exist, but there is no unified benchmarking standard representing the complexities of AIRR-seq data, obscuring objective comparisons of aligners across tasks. Here, we introduce GenAIRR, a modular simulation framework for generating Ig sequences alongside their ground truths. GenAIRR realistically simulates the intricacies of V(D)J recombination, somatic hypermutation, and an array of sequence corruptions. We comprehensively assessed prominent Ig sequence aligners across various metrics, unveiling unique performance characteristics for each aligner. The GenAIRR-produced datasets, combined with the proposed rigorous evaluation criteria, establish a solid basis for unbiased benchmarking of immunogenetics computational tools. It sets up the ground for further improving the crucial task of Ig sequence alignment, ultimately enhancing our understanding of adaptive immunity.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11531861PMC
http://dx.doi.org/10.1093/bib/bbae556DOI Listing

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