RCytoGPS: an R package for reading and visualizing cytogenetics data

Author:

Abrams Zachary B1ORCID,Tally Dwayne G2,Abruzzo Lynne V3,Coombes Kevin R4ORCID

Affiliation:

1. Department of Biostatistics, Institute for Informatics, Washington University in St. Louis, St. Louis, MO 63108, USA

2. Department of Biology, Indiana State University, Terre Haute, IN 47809, USA

3. Department of Pathology, Wexner Medical Center, The Ohio State University, Columbus, OH 43210, USA

4. Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA

Abstract

Abstract Summary Cytogenetics data, or karyotypes, are among the most common clinically used forms of genetic data. Karyotypes are stored as standardized text strings using the International System for Human Cytogenomic Nomenclature (ISCN). Historically, these data have not been used in large-scale computational analyses due to limitations in the ISCN text format and structure. Recently developed computational tools such as CytoGPS have enabled large-scale computational analyses of karyotypes. To further enable such analyses, we have now developed RCytoGPS, an R package that takes JSON files generated from CytoGPS.org and converts them into objects in R. This conversion facilitates the analysis and visualizations of karyotype data. In effect this tool streamlines the process of performing large-scale karyotype analyses, thus advancing the field of computational cytogenetic pathology. Availability and implementation Freely available at https://CRAN.R-project.org/package=RCytoGPS. The code for the underlying CytoGPS software can be found at https://github.com/i2-wustl/CytoGPS

Funder

National Library of Medicine

National Cancer Institute

Pelotonia Intramural Research Funds

NIH

Big Data for Indiana State University

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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