Partial least squares correspondence analysis: A framework to simultaneously analyze behavioral and genetic data.
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| Title: | Partial least squares correspondence analysis: A framework to simultaneously analyze behavioral and genetic data. |
|---|---|
| Authors: | Beaton, Derek, Dunlop, Joseph, Abdi, Hervé |
| Source: | Psychological Methods. Dec2016, Vol. 21 Issue 4, p621-651. 31p. |
| Abstract: | For nearly a century, detecting the genetic contributions to cognitive and behavioral phenomena has been a core interest for psychological research. Recently, this interest has been reinvigorated by the availability of genotyping technologies (e.g., microarrays) that provide new genetic data, such as single nucleotide polymorphisms (SNPs). These SNPs--which represent pairs of nucleotide letters (e.g., AA, AG, or GG) found at specific positions on human chromosomes--are best considered as categorical variables, but this coding scheme can make difficult the multivariate analysis of their relationships with behavioral measurements, because most multivariate techniques developed for the analysis between sets of variables are designed for quantitative variables. To palliate this problem, we present a generalization of partial least squares--a technique used to extract the information common to 2 different data tables measured on the same observations--called partial least squares correspondence analysis--that is specifically tailored for the analysis of categorical and mixed ("heterogeneous") data types. Here, we formally define and illustrate--in a tutorial format--how partial least squares correspondence analysis extends to various types of data and design problems that are particularly relevant for psychological research that include genetic data. We illustrate partial least squares correspondence analysis with genetic, behavioral, and neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative. R code is available on the Comprehensive R Archive Network and via the authors' websites. [ABSTRACT FROM AUTHOR] |
| Copyright of Psychological Methods is the property of American Psychological Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Education Research Complete |
| FullText | Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 120389744 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Partial least squares correspondence analysis: A framework to simultaneously analyze behavioral and genetic data. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Beaton%2C+Derek%22">Beaton, Derek</searchLink><br /><searchLink fieldCode="AR" term="%22Dunlop%2C+Joseph%22">Dunlop, Joseph</searchLink><br /><searchLink fieldCode="AR" term="%22Abdi%2C+Hervé%22">Abdi, Hervé</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Psychological+Methods%22">Psychological Methods</searchLink>. Dec2016, Vol. 21 Issue 4, p621-651. 31p. – Name: Abstract Label: Abstract Group: Ab Data: For nearly a century, detecting the genetic contributions to cognitive and behavioral phenomena has been a core interest for psychological research. Recently, this interest has been reinvigorated by the availability of genotyping technologies (e.g., microarrays) that provide new genetic data, such as single nucleotide polymorphisms (SNPs). These SNPs--which represent pairs of nucleotide letters (e.g., AA, AG, or GG) found at specific positions on human chromosomes--are best considered as categorical variables, but this coding scheme can make difficult the multivariate analysis of their relationships with behavioral measurements, because most multivariate techniques developed for the analysis between sets of variables are designed for quantitative variables. To palliate this problem, we present a generalization of partial least squares--a technique used to extract the information common to 2 different data tables measured on the same observations--called partial least squares correspondence analysis--that is specifically tailored for the analysis of categorical and mixed ("heterogeneous") data types. Here, we formally define and illustrate--in a tutorial format--how partial least squares correspondence analysis extends to various types of data and design problems that are particularly relevant for psychological research that include genetic data. We illustrate partial least squares correspondence analysis with genetic, behavioral, and neuroimaging data from the Alzheimer's Disease Neuroimaging Initiative. R code is available on the Comprehensive R Archive Network and via the authors' websites. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Psychological Methods is the property of American Psychological Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1037/met0000053 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 31 StartPage: 621 Titles: – TitleFull: Partial least squares correspondence analysis: A framework to simultaneously analyze behavioral and genetic data. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Beaton, Derek – PersonEntity: Name: NameFull: Dunlop, Joseph – PersonEntity: Name: NameFull: Abdi, Hervé IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2016 Type: published Y: 2016 Identifiers: – Type: issn-print Value: 1082989X Numbering: – Type: volume Value: 21 – Type: issue Value: 4 Titles: – TitleFull: Psychological Methods Type: main |
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