A collection of read depth profiles at structural variant breakpoints
Abstract SWaveform, a newly created open genome-wide resource for read depth signal in the vicinity of structural variant (SV) breakpoints, aims to boost development of computational tools and algorithms for discovery of genomic rearrangement events from sequencing data. SVs are a dominant force sha...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-04-01
|
| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-023-02076-4 |
| _version_ | 1797850243755147264 |
|---|---|
| author | Igor Bezdvornykh Nikolay Cherkasov Alexander Kanapin Anastasia Samsonova |
| author_facet | Igor Bezdvornykh Nikolay Cherkasov Alexander Kanapin Anastasia Samsonova |
| author_sort | Igor Bezdvornykh |
| collection | DOAJ |
| description | Abstract SWaveform, a newly created open genome-wide resource for read depth signal in the vicinity of structural variant (SV) breakpoints, aims to boost development of computational tools and algorithms for discovery of genomic rearrangement events from sequencing data. SVs are a dominant force shaping genomes and substantially contributing to genetic diversity. Still, there are challenges in reliable and efficient genotyping of SVs from whole genome sequencing data, thus delaying translation into clinical applications and wasting valuable resources. SWaveform includes a database containing ~7 M of read depth profiles at SV breakpoints extracted from 911 sequencing samples generated by the Human Genome Diversity Project, generalised patterns of the signal at breakpoints, an interface for navigation and download, as well as a toolbox for local deployment with user’s data. The dataset can be of immense value to bioinformatics and engineering communities as it empowers smooth application of intelligent signal processing and machine learning techniques for discovery of genomic rearrangement events and thus opens the floodgates for development of innovative algorithms and software. |
| first_indexed | 2024-04-09T18:57:15Z |
| format | Article |
| id | doaj.art-90b2987792c44e4b88544af8ac3b5db7 |
| institution | Directory Open Access Journal |
| issn | 2052-4463 |
| language | English |
| last_indexed | 2024-04-09T18:57:15Z |
| publishDate | 2023-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Data |
| spelling | doaj.art-90b2987792c44e4b88544af8ac3b5db72023-04-09T11:07:31ZengNature PortfolioScientific Data2052-44632023-04-011011910.1038/s41597-023-02076-4A collection of read depth profiles at structural variant breakpointsIgor Bezdvornykh0Nikolay Cherkasov1Alexander Kanapin2Anastasia Samsonova3Institute of Translational Biomedicine, Saint Petersburg State UniversityInstitute of Translational Biomedicine, Saint Petersburg State UniversityInstitute of Translational Biomedicine, Saint Petersburg State UniversityInstitute of Translational Biomedicine, Saint Petersburg State UniversityAbstract SWaveform, a newly created open genome-wide resource for read depth signal in the vicinity of structural variant (SV) breakpoints, aims to boost development of computational tools and algorithms for discovery of genomic rearrangement events from sequencing data. SVs are a dominant force shaping genomes and substantially contributing to genetic diversity. Still, there are challenges in reliable and efficient genotyping of SVs from whole genome sequencing data, thus delaying translation into clinical applications and wasting valuable resources. SWaveform includes a database containing ~7 M of read depth profiles at SV breakpoints extracted from 911 sequencing samples generated by the Human Genome Diversity Project, generalised patterns of the signal at breakpoints, an interface for navigation and download, as well as a toolbox for local deployment with user’s data. The dataset can be of immense value to bioinformatics and engineering communities as it empowers smooth application of intelligent signal processing and machine learning techniques for discovery of genomic rearrangement events and thus opens the floodgates for development of innovative algorithms and software.https://doi.org/10.1038/s41597-023-02076-4 |
| spellingShingle | Igor Bezdvornykh Nikolay Cherkasov Alexander Kanapin Anastasia Samsonova A collection of read depth profiles at structural variant breakpoints Scientific Data |
| title | A collection of read depth profiles at structural variant breakpoints |
| title_full | A collection of read depth profiles at structural variant breakpoints |
| title_fullStr | A collection of read depth profiles at structural variant breakpoints |
| title_full_unstemmed | A collection of read depth profiles at structural variant breakpoints |
| title_short | A collection of read depth profiles at structural variant breakpoints |
| title_sort | collection of read depth profiles at structural variant breakpoints |
| url | https://doi.org/10.1038/s41597-023-02076-4 |
| work_keys_str_mv | AT igorbezdvornykh acollectionofreaddepthprofilesatstructuralvariantbreakpoints AT nikolaycherkasov acollectionofreaddepthprofilesatstructuralvariantbreakpoints AT alexanderkanapin acollectionofreaddepthprofilesatstructuralvariantbreakpoints AT anastasiasamsonova acollectionofreaddepthprofilesatstructuralvariantbreakpoints AT igorbezdvornykh collectionofreaddepthprofilesatstructuralvariantbreakpoints AT nikolaycherkasov collectionofreaddepthprofilesatstructuralvariantbreakpoints AT alexanderkanapin collectionofreaddepthprofilesatstructuralvariantbreakpoints AT anastasiasamsonova collectionofreaddepthprofilesatstructuralvariantbreakpoints |