needLR: Long-read structural variant annotation with population-scale frequency estimation.

Authors

Jonas A Gustafson, Jiadong Lin, Miranda P G Zalusky, Evan E Eichler, Danny E Miller

Published in

Bioinformatics (Oxford, England). Jun 17, 2026. Epub Jun 17, 2026.

Abstract

We present needLR, a structural variant (SV) annotation tool that can be used for filtering and prioritization of candidate pathogenic SVs from long-read sequencing data using population allele frequencies, annotations for genomic context, and gene-phenotype associations. When using population data from 500 presumably healthy individuals to evaluate nine test cases with known pathogenic SVs, needLR assigned allele frequencies to over 97.5% of all detected SVs and reduced the average number of novel genic SVs to 121 per case while retaining all known pathogenic variants.
needLR is implemented in bash with dependencies including Truvari v4.2.2, BEDTools v2.31.1, and BCFtools v1.19. Source code, documentation, and pre-computed population allele frequency data are freely available at https://github.com/jgust1/needLR under an MIT license and archived on Zenodo at https://zenodo.org/records/19463479.

PMID:
42308524
Bibliographic data and abstract were imported from PubMed on 18 Jun 2026.

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