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Partial least squares correspondence analysis: A framework to simultaneously analyze behavioral and genetic data.

Derek Beaton1, Joseph Dunlop2, Hervé Abdi1

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This study introduces partial least squares correspondence analysis, a new method for analyzing genetic and behavioral data. This technique helps uncover genetic influences on cognition and behavior by handling categorical genetic data effectively.

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Area of Science:

  • Psychological research
  • Genetics
  • Neuroimaging

Background:

  • Detecting genetic contributions to cognition and behavior is a long-standing interest in psychology.
  • Genotyping technologies like microarrays provide new genetic data, such as single nucleotide polymorphisms (SNPs).
  • Multivariate analysis of SNPs with behavioral data is challenging due to SNPs being categorical variables.

Purpose of the Study:

  • To present a generalization of partial least squares called partial least squares correspondence analysis (PLS-CA).
  • To tailor PLS-CA for the analysis of categorical and mixed data types common in psychological and genetic research.
  • To provide a tutorial on applying PLS-CA to various data types and design problems.

Main Methods:

  • Partial least squares correspondence analysis (PLS-CA), a technique for analyzing relationships between two data tables.
  • Application to heterogeneous data, including genetic, behavioral, and neuroimaging data.
  • Illustration using data from the Alzheimer's Disease Neuroimaging Initiative.

Main Results:

  • PLS-CA effectively analyzes categorical and mixed data, overcoming limitations of traditional multivariate techniques.
  • The method facilitates the exploration of common information between genetic and behavioral datasets.
  • Demonstrated utility in a real-world dataset relevant to neurological research.

Conclusions:

  • Partial least squares correspondence analysis is a powerful tool for psychological research involving genetic data.
  • This method enhances the ability to study the genetic underpinnings of cognitive and behavioral phenomena.
  • The R code is available for broader application in the scientific community.