Niehus, Sebastian and Jonsson, Hakon and Schoenberger, Janina and Bjornsson, Eythor and Beyter, Doruk and Eggertsson, Hannes P. and Sulem, Patrick and Stefansson, Kari and Halldorsson, Bjarni and Kehr, Birte (2021) PopDel identifies medium-size deletions simultaneously in tens of thousands of genomes. NATURE COMMUNICATIONS, 12 (1): 730. ISSN , 2041-1723
Full text not available from this repository. (Request a copy)Abstract
Thousands of genomic structural variants (SVs) segregate in the human population and can impact phenotypic traits and diseases. Their identification in whole-genome sequence data of large cohorts is a major computational challenge. Most current approaches identify SVs in single genomes and afterwards merge the identified variants into a joint call set across many genomes. We describe the approach PopDel, which directly identifies deletions of about 500 to at least 10,000bp in length in data of many genomes jointly, eliminating the need for subsequent variant merging. PopDel scales to tens of thousands of genomes as we demonstrate in evaluations on up to 49,962 genomes. We show that PopDel reliably reports common, rare and de novo deletions. On genomes with available high-confidence reference call sets PopDel shows excellent recall and precision. Genotype inheritance patterns in up to 6794 trios indicate that genotypes predicted by PopDel are more reliable than those of previous SV callers. Furthermore, PopDel's running time is competitive with the fastest tested previous tools. The demonstrated scalability and accuracy of PopDel enables routine scans for deletions in large-scale sequencing studies. Identifying structural variants (SVs) from whole genome sequence data has been a significant bioinformatic challenge. Here, the authors describe PopDel, which uses a joint SV detection approach to reliably and efficiently identify 500-10,000bp deletions across large population cohorts.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | STRUCTURAL VARIATION; READ ALIGNMENT; GC-CONTENT; ACCURATE; RESOURCE; GENES; |
| Subjects: | 600 Technology > 610 Medical sciences Medicine |
| Divisions: | Medicine > Zentren des Universitätsklinikums Regensburg > Regensburger Centrum für Interventionelle Immunologie (RCI) |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 29 Aug 2022 07:30 |
| Last Modified: | 29 Aug 2022 07:30 |
| URI: | https://pred.uni-regensburg.de/id/eprint/46400 |
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