A collection of read depth profiles at structural variant breakpoints

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A collection of read depth profiles at structural variant breakpoints. / Bezdvornykh, Igor ; Cherkasov, Nikolay ; Kanapin, Alexander ; Samsonova, Anastasia .

In: Nature Scientific Data, Vol. 10, No. 1, 186, 06.04.2023.

Research output: Contribution to journal › Article › peer-review

Author

Bezdvornykh, Igor ; Cherkasov, Nikolay ; Kanapin, Alexander ; Samsonova, Anastasia . / A collection of read depth profiles at structural variant breakpoints. In: Nature Scientific Data. 2023 ; Vol. 10, No. 1.

BibTeX

@article{cd3e32b481f74e7093c86875a5022d55,

title = "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 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.",

keywords = "Data processing, Genetic databases, Software, Algorithms, Humans, Genomics, High-Throughput Nucleotide Sequencing, Genome, Human, Sequence Analysis, DNA/methods",

author = "Igor Bezdvornykh and Nikolay Cherkasov and Alexander Kanapin and Anastasia Samsonova",

note = "Bezdvornykh, I., Cherkasov, N., Kanapin, A. et al. A collection of read depth profiles at structural variant breakpoints. Sci Data 10, 186 (2023). https://doi.org/10.1038/s41597-023-02076-4",

year = "2023",

month = apr,

day = "6",

doi = "10.1038/s41597-023-02076-4",

language = "English",

volume = "10",

journal = "Scientific data",

issn = "2052-4463",

publisher = "Nature Publishing Group",

number = "1",

}

RIS

TY - JOUR

T1 - A collection of read depth profiles at structural variant breakpoints

AU - Bezdvornykh, Igor

AU - Cherkasov, Nikolay

AU - Kanapin, Alexander

AU - Samsonova, Anastasia

N1 - Bezdvornykh, I., Cherkasov, N., Kanapin, A. et al. A collection of read depth profiles at structural variant breakpoints. Sci Data 10, 186 (2023). https://doi.org/10.1038/s41597-023-02076-4

PY - 2023/4/6

Y1 - 2023/4/6

N2 - 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.

AB - 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.

KW - Data processing

KW - Genetic databases

KW - Software

KW - Algorithms

KW - Humans

KW - Genomics

KW - High-Throughput Nucleotide Sequencing

KW - Genome, Human

KW - Sequence Analysis, DNA/methods

UR - https://www.mendeley.com/catalogue/f0020edf-2f4f-3c6c-a5a6-806fe5563a0b/

U2 - 10.1038/s41597-023-02076-4

DO - 10.1038/s41597-023-02076-4

M3 - Article

C2 - 37024526

VL - 10

JO - Scientific data

JF - Scientific data

SN - 2052-4463

IS - 1

M1 - 186

ER -

ID: 106363910