Book contents
- Multivariate Biomarker Discovery
- Multivariate Biomarker Discovery
- Copyright page
- Dedication
- Contents
- Preface
- Acknowledgments
- Part I Framework for Multivariate Biomarker Discovery
- Part II Regression Methods for Estimation
- Part III Classification Methods
- Part IV Biomarker Discovery via Multistage Signal Enhancement and Identification of Essential Patterns
- Part V Multivariate Biomarker Discovery Studies
- 16 Biomarker Discovery Study 1
- 17 Biomarker Discovery Study 2
- References
- Index
16 - Biomarker Discovery Study 1
Searching for Essential Gene Expression Patterns and Multivariate Biomarkers That Are Common for Multiple Types of Cancers
from Part V - Multivariate Biomarker Discovery Studies
Published online by Cambridge University Press: 30 May 2024
- Multivariate Biomarker Discovery
- Multivariate Biomarker Discovery
- Copyright page
- Dedication
- Contents
- Preface
- Acknowledgments
- Part I Framework for Multivariate Biomarker Discovery
- Part II Regression Methods for Estimation
- Part III Classification Methods
- Part IV Biomarker Discovery via Multistage Signal Enhancement and Identification of Essential Patterns
- Part V Multivariate Biomarker Discovery Studies
- 16 Biomarker Discovery Study 1
- 17 Biomarker Discovery Study 2
- References
- Index
Summary
Chapters 16 presents the first of the two real-life multivariate biomarker discovery studies included in the book. The goal of this study – which implements the method presented in Chapters 14 and 15 – is to identify the essential gene expression patterns and a multivariate biomarker common for multiple types of cancer. This study is based on the TCGA RNA-Seq data of 3,528 patients and 20,530 gene expression variables; the data represent five tumor types of five different tissues. A parsimonious multivariate biomarker (consisting of ten genes) with high sensitivity and specificity has been identified.
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- Multivariate Biomarker DiscoveryData Science Methods for Efficient Analysis of High-Dimensional Biomedical Data, pp. 221 - 240Publisher: Cambridge University PressPrint publication year: 2024