Statistics for microarrays [[electronic resource] ] : design, analysis, and inference / / Ernst Wit and John McClure |
Autore | Wit Ernst |
Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, USA, : John Wiley & Sons, c2004 |
Descrizione fisica | 1 online resource (279 p.) |
Disciplina | 629.04 |
Altri autori (Persone) | McClureJohn D |
Soggetto topico | DNA microarrays - Statistical methods |
ISBN |
1-280-27447-6
9786610274475 0-470-01107-6 0-470-01108-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Contents; Preface; 1 Preliminaries; 1.1 Using the R Computing Environment; 1.1.1 Installing smida; 1.1.2 Loading smida; 1.2 Data Sets from Biological Experiments; 1.2.1 Arabidopsis experiment: Anna Amtmann; 1.2.2 Skin cancer experiment: Nighean Barr; 1.2.3 Breast cancer experiment: John Bartlett; 1.2.4 Mammary gland experiment: Gusterson group; 1.2.5 Tuberculosis experiment: BμG@S group; I: Getting Good Data; 2 Set-up of a Microarray Experiment; 2.1 Nucleic Acids: DNA and RNA; 2.2 Simple cDNA Spotted Microarray Experiment; 3 Statistical Design of Microarrays; 3.1 Sources of Variation
3.2 Replication3.3 Design Principles; 3.4 Single-channel Microarray Design; 3.5 Two-channel Microarray Designs; 4 Normalization; 4.1 Image Analysis; 4.2 Introduction to Normalization; 4.3 Normalization for Dual-channel Arrays; 4.4 Normalization of Single-channel Arrays; 5 Quality Assessment; 5.1 Using MIAME in Quality Assessment; 5.2 Comparing Multivariate Data; 5.3 Detecting Data Problems; 5.4 Consequences of Quality Assessment Checks; 6 Microarray Myths: Data; 6.1 Design; 6.2 Normalization; II: Getting Good Answers; 7 Microarray Discoveries; 7.1 Discovering Sample Classes 7.2 Exploratory Supervised Learning7.3 Discovering Gene Clusters; 8 Differential Expression; 8.1 Introduction; 8.2 Classical Hypothesis Testing; 8.3 Bayesian Hypothesis Testing; 9 Predicting Outcomes with Gene Expression Profiles; 9.1 Introduction; 9.2 Curse of Dimensionality: Gene Filtering; 9.3 Predicting Class Memberships; 9.4 Predicting Continuous Responses; 10 Microarray Myths: Inference; 10.1 Differential Expression; 10.2 Prediction and Learning; Bibliography; Index; A; B; C; D; E; F; G; H; I; K; L; M; N; O; P; Q; R; S; T; U; V; W |
Record Nr. | UNINA-9910145753603321 |
Wit Ernst
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Chichester, England ; ; Hoboken, NJ, USA, : John Wiley & Sons, c2004 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
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Statistics for microarrays [[electronic resource] ] : design, analysis, and inference / / Ernst Wit and John McClure |
Autore | Wit Ernst |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, USA, : John Wiley & Sons, c2004 |
Descrizione fisica | 1 online resource (279 p.) |
Disciplina | 629.04 |
Altri autori (Persone) | McClureJohn D |
Soggetto topico | DNA microarrays - Statistical methods |
ISBN |
1-280-27447-6
9786610274475 0-470-01107-6 0-470-01108-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Contents; Preface; 1 Preliminaries; 1.1 Using the R Computing Environment; 1.1.1 Installing smida; 1.1.2 Loading smida; 1.2 Data Sets from Biological Experiments; 1.2.1 Arabidopsis experiment: Anna Amtmann; 1.2.2 Skin cancer experiment: Nighean Barr; 1.2.3 Breast cancer experiment: John Bartlett; 1.2.4 Mammary gland experiment: Gusterson group; 1.2.5 Tuberculosis experiment: BμG@S group; I: Getting Good Data; 2 Set-up of a Microarray Experiment; 2.1 Nucleic Acids: DNA and RNA; 2.2 Simple cDNA Spotted Microarray Experiment; 3 Statistical Design of Microarrays; 3.1 Sources of Variation
3.2 Replication3.3 Design Principles; 3.4 Single-channel Microarray Design; 3.5 Two-channel Microarray Designs; 4 Normalization; 4.1 Image Analysis; 4.2 Introduction to Normalization; 4.3 Normalization for Dual-channel Arrays; 4.4 Normalization of Single-channel Arrays; 5 Quality Assessment; 5.1 Using MIAME in Quality Assessment; 5.2 Comparing Multivariate Data; 5.3 Detecting Data Problems; 5.4 Consequences of Quality Assessment Checks; 6 Microarray Myths: Data; 6.1 Design; 6.2 Normalization; II: Getting Good Answers; 7 Microarray Discoveries; 7.1 Discovering Sample Classes 7.2 Exploratory Supervised Learning7.3 Discovering Gene Clusters; 8 Differential Expression; 8.1 Introduction; 8.2 Classical Hypothesis Testing; 8.3 Bayesian Hypothesis Testing; 9 Predicting Outcomes with Gene Expression Profiles; 9.1 Introduction; 9.2 Curse of Dimensionality: Gene Filtering; 9.3 Predicting Class Memberships; 9.4 Predicting Continuous Responses; 10 Microarray Myths: Inference; 10.1 Differential Expression; 10.2 Prediction and Learning; Bibliography; Index; A; B; C; D; E; F; G; H; I; K; L; M; N; O; P; Q; R; S; T; U; V; W |
Record Nr. | UNISA-996213669903316 |
Wit Ernst
![]() |
||
Chichester, England ; ; Hoboken, NJ, USA, : John Wiley & Sons, c2004 | ||
![]() | ||
Lo trovi qui: Univ. di Salerno | ||
|
Statistics for microarrays : design, analysis, and inference / / Ernst Wit and John McClure |
Autore | Wit Ernst |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Chichester, England ; ; Hoboken, NJ, USA, : John Wiley & Sons, c2004 |
Descrizione fisica | 1 online resource (279 p.) |
Disciplina | 629.04 |
Altri autori (Persone) | McClureJohn D |
Soggetto topico | DNA microarrays - Statistical methods |
ISBN |
1-280-27447-6
9786610274475 0-470-01107-6 0-470-01108-4 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Contents; Preface; 1 Preliminaries; 1.1 Using the R Computing Environment; 1.1.1 Installing smida; 1.1.2 Loading smida; 1.2 Data Sets from Biological Experiments; 1.2.1 Arabidopsis experiment: Anna Amtmann; 1.2.2 Skin cancer experiment: Nighean Barr; 1.2.3 Breast cancer experiment: John Bartlett; 1.2.4 Mammary gland experiment: Gusterson group; 1.2.5 Tuberculosis experiment: BμG@S group; I: Getting Good Data; 2 Set-up of a Microarray Experiment; 2.1 Nucleic Acids: DNA and RNA; 2.2 Simple cDNA Spotted Microarray Experiment; 3 Statistical Design of Microarrays; 3.1 Sources of Variation
3.2 Replication3.3 Design Principles; 3.4 Single-channel Microarray Design; 3.5 Two-channel Microarray Designs; 4 Normalization; 4.1 Image Analysis; 4.2 Introduction to Normalization; 4.3 Normalization for Dual-channel Arrays; 4.4 Normalization of Single-channel Arrays; 5 Quality Assessment; 5.1 Using MIAME in Quality Assessment; 5.2 Comparing Multivariate Data; 5.3 Detecting Data Problems; 5.4 Consequences of Quality Assessment Checks; 6 Microarray Myths: Data; 6.1 Design; 6.2 Normalization; II: Getting Good Answers; 7 Microarray Discoveries; 7.1 Discovering Sample Classes 7.2 Exploratory Supervised Learning7.3 Discovering Gene Clusters; 8 Differential Expression; 8.1 Introduction; 8.2 Classical Hypothesis Testing; 8.3 Bayesian Hypothesis Testing; 9 Predicting Outcomes with Gene Expression Profiles; 9.1 Introduction; 9.2 Curse of Dimensionality: Gene Filtering; 9.3 Predicting Class Memberships; 9.4 Predicting Continuous Responses; 10 Microarray Myths: Inference; 10.1 Differential Expression; 10.2 Prediction and Learning; Bibliography; Index; A; B; C; D; E; F; G; H; I; K; L; M; N; O; P; Q; R; S; T; U; V; W |
Record Nr. | UNINA-9910813379003321 |
Wit Ernst
![]() |
||
Chichester, England ; ; Hoboken, NJ, USA, : John Wiley & Sons, c2004 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|