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KinVis: a visualization tool to detect cryptic relatedness in genetic datasets.
Ullah, Ehsan; Aupetit, Michaël; Das, Arun; Patil, Abhishek; Al Muftah, Noora; Rawi, Reda; Saad, Mohamad; Bensmail, Halima.
Afiliação
  • Ullah E; Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar.
  • Aupetit M; Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar.
  • Das A; Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar.
  • Patil A; Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar.
  • Al Muftah N; Department of Computational Biology and Quantitative Genetics, Harvard School of Public Health, Boston, MA, USA.
  • Rawi R; Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar.
  • Saad M; Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA.
  • Bensmail H; Qatar Computing Research Institute, Hamad Bin Khalifa University, Doha, Qatar.
Bioinformatics ; 35(15): 2683-2685, 2019 08 01.
Article em En | MEDLINE | ID: mdl-30590437
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Estudo de Associação Genômica Ampla Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Qatar

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Estudo de Associação Genômica Ampla Idioma: En Revista: Bioinformatics Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Qatar