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digit - a tool for detection and identification of genomic interchromosomal translocations

Title:
digit - a tool for detection and identification of genomic interchromosomal translocations
Abstract:
Structural variations (SVs) in genomic DNA can have profound effects on the evolution of living organisms, on phenotypic variations and on disease processes. A critical step in discovering the full extent of structural variations is the development of tools to characterize these variations accurately in next generation sequencing data. Toward this goal, we developed a software pipeline named digit that implements a novel measure of mapping ambiguity to discover interchromosomal SVs from mate-pair and pair-end sequencing data. The workflow robustly handles the high numbers of artifacts present in mate-pair sequencing and reduces the false positive rate while maintaining sensitivity. In the simulated data set, our workflow recovered 96% of simulated SVs. It generates a self-updating library of common translocations and allows for the investigation of patient- or group-specific events, making it suitable for discovering and cataloging chromosomal translocations associated with specific groups, traits, diseases or population structures.
Year:
2017
Publication type:
Journal article
Journal:
Nucleic Acids Research
ISSN:
1362-4962
Number:
9
Volume:
45
Pages:
e72
Language:
English
Document status:
Open access
PubListerURL:
https://publister.bib.th-wildau.de/publister/public/publication/2256
Meier, R., Graw, S., Beyerlein, P., Koestler, D., Molina, J., & Chien, J. (2017). digit - a tool for detection and identification of genomic interchromosomal translocations Nucleic Acids Research. 45 (9), e72.
@article{2256,
    author           = {Meier, Richard and Graw, Stefan and Beyerlein, Peter and Koestler, Devin and Molina, Julian R. and Chien, Jeremy},
    title            = {digit - a tool for detection and identification of genomic interchromosomal translocations},
    journal          = {Nucleic Acids Research},
    year             = {2017},
    volume           = {45},
    number           = {9},
    pages            = {e72},
    publisher        = {Oxford University Press},
    doi              = {10.1093/nar/gkx010},
}


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