Cargando…

CytoGPS: a web-enabled karyotype analysis tool for cytogenetics

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 def...

Descripción completa

Detalles Bibliográficos
Autores principales: Abrams, Zachary B, Zhang, Lin, Abruzzo, Lynne V, Heerema, Nyla A, Li, Suli, Dillon, Tom, Rodriguez, Ricky, Coombes, Kevin R, Payne, Philip R O
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954647/
https://www.ncbi.nlm.nih.gov/pubmed/31263896
http://dx.doi.org/10.1093/bioinformatics/btz520
_version_ 1783486839180492800
author Abrams, Zachary B
Zhang, Lin
Abruzzo, Lynne V
Heerema, Nyla A
Li, Suli
Dillon, Tom
Rodriguez, Ricky
Coombes, Kevin R
Payne, Philip R O
author_facet Abrams, Zachary B
Zhang, Lin
Abruzzo, Lynne V
Heerema, Nyla A
Li, Suli
Dillon, Tom
Rodriguez, Ricky
Coombes, Kevin R
Payne, Philip R O
author_sort Abrams, Zachary B
collection PubMed
description 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.
format Online
Article
Text
id pubmed-6954647
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-69546472020-01-16 CytoGPS: a web-enabled karyotype analysis tool for cytogenetics Abrams, Zachary B Zhang, Lin Abruzzo, Lynne V Heerema, Nyla A Li, Suli Dillon, Tom Rodriguez, Ricky Coombes, Kevin R Payne, Philip R O Bioinformatics Applications Notes 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. Oxford University Press 2019-12-15 2019-07-02 /pmc/articles/PMC6954647/ /pubmed/31263896 http://dx.doi.org/10.1093/bioinformatics/btz520 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Applications Notes
Abrams, Zachary B
Zhang, Lin
Abruzzo, Lynne V
Heerema, Nyla A
Li, Suli
Dillon, Tom
Rodriguez, Ricky
Coombes, Kevin R
Payne, Philip R O
CytoGPS: a web-enabled karyotype analysis tool for cytogenetics
title CytoGPS: a web-enabled karyotype analysis tool for cytogenetics
title_full CytoGPS: a web-enabled karyotype analysis tool for cytogenetics
title_fullStr CytoGPS: a web-enabled karyotype analysis tool for cytogenetics
title_full_unstemmed CytoGPS: a web-enabled karyotype analysis tool for cytogenetics
title_short CytoGPS: a web-enabled karyotype analysis tool for cytogenetics
title_sort cytogps: a web-enabled karyotype analysis tool for cytogenetics
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954647/
https://www.ncbi.nlm.nih.gov/pubmed/31263896
http://dx.doi.org/10.1093/bioinformatics/btz520
work_keys_str_mv AT abramszacharyb cytogpsawebenabledkaryotypeanalysistoolforcytogenetics
AT zhanglin cytogpsawebenabledkaryotypeanalysistoolforcytogenetics
AT abruzzolynnev cytogpsawebenabledkaryotypeanalysistoolforcytogenetics
AT heeremanylaa cytogpsawebenabledkaryotypeanalysistoolforcytogenetics
AT lisuli cytogpsawebenabledkaryotypeanalysistoolforcytogenetics
AT dillontom cytogpsawebenabledkaryotypeanalysistoolforcytogenetics
AT rodriguezricky cytogpsawebenabledkaryotypeanalysistoolforcytogenetics
AT coombeskevinr cytogpsawebenabledkaryotypeanalysistoolforcytogenetics
AT paynephilipro cytogpsawebenabledkaryotypeanalysistoolforcytogenetics