Outlier detection for questionnaire data in biobanks.

Journal: International journal of epidemiology
Published Date: Aug 1, 2019

Abstract

BACKGROUND: Biobanks increasingly collect, process and store omics with more conventional epidemiologic information necessitating considerable effort in data cleaning. An efficient outlier detection method that reduces manual labour is highly desirable.

Authors

  • Rieko Sakurai
    Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.
  • Masao Ueki
    Tohoku Medical Megabank Organization (ToMMo), Tohoku University, Sendai, Miyagi, Japan.
  • Satoshi Makino
    Statistical Genetics Team, RIKEN Center for Advanced Intelligence Project, Tokyo, Japan.
  • Atsushi Hozawa
    Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
  • Shinichi Kuriyama
    Tohoku Medical Megabank Organization (ToMMo), Tohoku University, Sendai, Miyagi, Japan. kuriyama@med.tohoku.ac.jp.
  • Takako Takai-Igarashi
    Tohoku Medical Megabank Organization, Tohoku University, Sendai, Japan.
  • Kengo Kinoshita
    Graduate School of Information Sciences, Tohoku University, Sendai, Japan. kengo@ecei.tohoku.ac.jp.
  • Masayuki Yamamoto
  • Gen Tamiya
    Tohoku Medical Megabank Organization (ToMMo), Tohoku University, Sendai, Miyagi, Japan.

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