Data Analysis and Chemometrics for Metabolomics

fmatter
	Title Page
	Copyright Page
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	2.2 Coupled Chromatography Mass Spectrometry
		2.2.2 Ionisation and Detection
			2.2.2.1 GCMS
			2.2.2.2 LCMS
		2.2.4 Step 1 of Creating a Peak Table: Transforming Chromatographic Data to an Aligned Matrix of Peaks
			2.2.4.1 XCMS
			2.2.4.2 Multivariate Curve Resolution
			2.2.4.3 AMDIS
			2.2.4.4 MZmine
			2.2.4.5 Other Approaches
			2.2.4.6 Which Approach is Most Suitable?
		2.2.6 Step 3 of Creating a Peak Table: Identifying Metabolites and Annotating the Peaks
			2.2.6.1 Experimental Libraries
			2.2.6.2 Computational Mass Spectral and Retention Libraries
			2.2.6.3 Expert Systems
	2.4 Nuclear Magnetic Resonance
		2.4.1 Fourier Transform Techniques
			2.4.1.1 FT Principles
			2.4.1.2 Resolution and Signal-to-Noise
		2.4.3 Preparing the Data Table
			2.4.3.1 Chemometric Approach
			2.4.3.2 Deconvolution and Identification
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	4.6 Transforming the Data
		4.6.1 Row Scaling
			4.6.1.1 Row Scaling to Constant Total
			4.6.1.2 Standard Normal Variates
			4.6.1.3 Scaling to Reference Standards
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	6.2 Design of Experiments
		6.2.3 Statistical Designs
			6.2.3.1 Fully Crossed Designs
			6.2.3.2 Two-level Full Factorial Designs
			6.2.3.3 Fractional Factorial Designs
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	7.4 Two-Class Classifiers
		7.4.2 Partial Least Squares Discriminant Analysis
			7.4.2.1 PLSDA for Equal Class Sizes
			7.4.2.2 PLSDA for Unequal Class Sizes
			7.4.2.3 OPLS
	7.5 One-Class Classifiers
		7.5.2 SIMCA
			7.5.2.1 Disjoint PCA
			7.5.2.2 D- and Q-statistics
			7.5.2.3 Limits and Decisions
	7.6 Multiclass Classifiers
		7.6.2 PLSDA as a Multiclass Classifier
			7.6.2.1 One Versus All
			7.6.2.2 One Versus One
			7.6.2.3 PLS2DA
	7.7 Validation, Optimisation and Performance Indicators
		7.7.1 Classification Performance
			7.7.1.1 Two Classes
			7.7.1.2 Multiclasses
			7.7.1.3 One-Class Models
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	10.3 Single Factor (One-Way – One-Factor) Anova Test And Regression
		10.3.1 Balanced Design at Two Levels
			10.3.1.1 Degrees of Freedom
			10.3.1.2 ANOVA Test
			10.3.1.3 Regression
			10.3.1.4 The t-test
		10.3.4 Multilevel Designs
			10.3.4.1 One-Way Multilevel ANOVA Test
			10.3.4.2 One-Way Multilevel Regression with Dummy Variables: Unrelated Groups
			10.3.4.3 One-Way Multilevel Multilinear Regression: Related Groups
			10.3.4.4 Comparison and Interpretation
	10.4 Multiple Factor (Multiway) ANOVA Test and Regression
		10.4.1 Simulated 2 × 3 Case Study: ANOVA Test and Regression
			10.4.1.1 ANOVA Test
			10.4.1.2 Regression with Dummy Variables