needLR: Long-read structural variant annotation with population-scale frequency estimation
Fuente:
arXiv
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866917133855752192 |
|---|---|
| author | Gustafson, Jonas A. Lin, Jiadong Eichler, Evan E. Miller, Danny E. |
| author_facet | Gustafson, Jonas A. Lin, Jiadong Eichler, Evan E. Miller, Danny E. |
| contents | Summary: 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. Availability and Implementation: 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_08175 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | needLR: Long-read structural variant annotation with population-scale frequency estimation Gustafson, Jonas A. Lin, Jiadong Eichler, Evan E. Miller, Danny E. Genomics Summary: 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. Availability and Implementation: 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. |
| title | needLR: Long-read structural variant annotation with population-scale frequency estimation |
| topic | Genomics |
| url | https://arxiv.org/abs/2512.08175 |