KinVis: a visualization tool to detect cryptic relatedness in genetic datasets

Ehsan Ullah; Michaël Aupetit; Arun Das; Abhishek Patil; Noora Al Muftah; Reda Rawi; Mohamad Saad; Halima Bensmail

doi:10.1093/bioinformatics/bty1028

KinVis: a visualization tool to detect cryptic relatedness in genetic datasets

Bioinformatics. 2019 Aug 1;35(15):2683-2685. doi: 10.1093/bioinformatics/bty1028.

Authors

Ehsan Ullah¹, Michaël Aupetit¹, Arun Das¹, Abhishek Patil¹, Noora Al Muftah², Reda Rawi^{1

3}, Mohamad Saad¹, Halima Bensmail¹

Affiliations

¹ Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar.
² Department of Computational Biology and Quantitative Genetics, Harvard School of Public Health, Boston, MA, USA.
³ Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA.

Abstract

Motivation: It is important to characterize individual relatedness in terms of familial relationships and underlying population structure in genome-wide association studies for correct downstream analysis. The characterization of individual relatedness becomes vital if the cohort is to be used as reference panel in other studies for association tests and for identifying ethnic diversities. In this paper, we propose a kinship visualization tool to detect cryptic relatedness between subjects. We utilize multi-dimensional scaling, bar charts, heat maps and node-link visualizations to enable analysis of relatedness information.

Availability and implementation: Available online as well as can be downloaded at http://shiny-vis.qcri.org/public/kinvis/.

Supplementary information: Supplementary data are available at Bioinformatics online.

MeSH terms

Genome-Wide Association Study*
Software*