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. 2019 Dec 15;35(24):5365-5366.
doi: 10.1093/bioinformatics/btz520.

CytoGPS: a web-enabled karyotype analysis tool for cytogenetics

Zachary B Abrams  1 , Lin Zhang  2 , Lynne V Abruzzo  3 , Nyla A Heerema  3 , Suli Li  1 , Tom Dillon  2 , Ricky Rodriguez  2 , Kevin R Coombes  1 , Philip R O Payne  2
Affiliations

CytoGPS: a web-enabled karyotype analysis tool for cytogenetics

Zachary B Abrams et al. Bioinformatics. .

Abstract

Summary: Karyotype data are the most common form of genetic data that is regularly used clinically. They are collected as part of the standard of care in many diseases, particularly in pediatric and cancer medicine contexts. Karyotypes are represented in a unique text-based format, with a syntax defined by the International System for human Cytogenetic Nomenclature (ISCN). While human-readable, ISCN is not intrinsically machine-readable. This limitation has prevented the full use of complex karyotype data in discovery science use cases. To enhance the utility and value of karyotype data, we developed a tool named CytoGPS. CytoGPS first parses ISCN karyotypes into a machine-readable format. It then converts the ISCN karyotype into a binary Loss-Gain-Fusion (LGF) model, which represents all cytogenetic abnormalities as combinations of loss, gain, or fusion events, in a format that is analyzable using modern computational methods. Such data is then made available for comprehensive 'downstream' analyses that previously were not feasible.

Availability and implementation: Freely available at http://cytogps.org.

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Figures

Fig. 1.
Fig. 1.
CytoGPS website. This shows the karyotype analysis landing page, which describes general information about how to use the web based analysis tool. The left panel shows how results are displayed after a karyotype has been parsed. The user is shown which chromosomes have cytogenetic abnormalities and is provided with a downloadable file of the results. When a user clicks on a chromosome, they see a table in the right panel that shows each cytogenetic region on that particular chromosome and how those regions were affected
See this image and copyright information in PMC

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References

    1. Abrams Z.B. et al. (2015) Text mining and data modeling of karyotypes to aid in drug repurposing efforts. Stud. Health Technol. Inform., 216, 1037. - PMC - PubMed
    1. McGowan-Jordan J. et al. (2016) ISCN 2016: An International System for Human Cytogenomic Nomenclature. Karger Medical and Scientific Publishers, Basel.
    1. Parr T. (2013) The Definitive ANTLR 4 Reference. Pragmatic Bookshelf, Dallas, TX.

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