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

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

Research output: Contribution to journalArticle

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.

Original languageEnglish
Pages (from-to)2683-2685
Number of pages3
JournalBioinformatics
Volume35
Issue number15
DOIs
Publication statusPublished - 1 Aug 2019

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ASJC Scopus subject areas

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

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