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Multivariate data integration using R : methods and applications with the mixOmics package / Kim-Anh L̊ Cao, Zoe Welham.

Lê Cao, Kim-Anh, author.; Welham, Zoe, author.; ProQuest (Firm)
2022
QH323.5 .L43 2022
Available Online
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Title
Multivariate data integration using R : methods and applications with the mixOmics package / Kim-Anh L̊ Cao, Zoe Welham.
Author
Lê Cao, Kim-Anh, author.
Edition
First edition.
ISBN
9781003026860 (electronic book)
1003026869 (electronic book)
9781000472264 (electronic book)
1000472264 (electronic book)
9781000472196 (electronic book)
1000472191 (electronic book)
9780367460945
0367460947
DOI
https://doi.org/10.1201/9781003026860
Published
Boca Raton, FL : CRC Press, Taylor & Francis Group, 2022.
Copyright
©2022
Language
English
Description
1 online resource (xxi, 308 pages) : illustrations.
Item Number
10.1201/9781003026860 doi
Call Number
QH323.5 .L43 2022
Dewey Decimal Classification
570.1/5195
Note
"A Chapman & Hall Book."
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users
Reproduction
Electronic reproduction. Ann Arbor, MI Available via World Wide Web.
Source of Description
Description based on online resource; title from digital title page (viewed on December 15, 2021).
Added Author
Welham, Zoe, author.
Added Corporate Author
ProQuest (Firm)
Series
Computational biology.
Available in Other Form
Multivariate data integration using R.
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Online Access
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Online Resources > Ebooks
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I Modern biology and multivariate analysis 1. Multi-omics and biological systems 2. The cycle of analysi3. Key multivariate concepts and dimension reduction in mixOmics . Choose the right method for the right question in mixOmics ixOmics under the hood 5. Projection to Latent Structures . Visualisation for data integration . Performance assessment in multivariate analyses II mixOmics in action . mixOmics: get started . Principal Component Analysis (PCA) 10 Projection to Latent Structure (PLS) 1. Canonical Correlation Analysis (CCA) 2. PLS
Discriminant Analysis (PLS-DA) 3. N data integration 4. P data integration 5. (APPENDIX) Glossary of Terms

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