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Название: Meta-analysis and combining information in genetics and genomics
Авторы: Guerra R., Goldstein D.
Аннотация:
Content: Pt. 0. Introductory Material — 1. brief introduction to meta-analysis, genetics, and genomics / Darlene R. Goldstein and Rudy Guerra — Pt I. Similar Data Types I: Genotype Data — 2. Combining information across genome-wide linkage scans / Carol J. Etzel and Tracy J. Costello — 3. Genome search meta-analysis (GSMA): a nonparametric method for meta-analysis of genome-wide linkage studies / Cathryn M. Lewis — 4. Heterogeneity in meta-analysis of quantitative trait linkage studies / Hans C. van Houwelingen and Jeremie J. P. Lebrec — 5. empirical Bayesian framework for QTL genome-wide scans / Kui Zhang ... [et al.] — Pt. II. Similar Data Types II: Gene Expression Data — 6. Composite hypothesis testing: an approach built on intersection-union tests and Bayesian posterior probabilities / Stephen Erickson, Kyoungmi Kim and David B. Allison — 7. Frequentist and Bayesian error pooling methods for enhancing statistical power in small sample microarray data analysis / Jae K. Lee, Hyung Jun Cho and Michael O'Connell — 8. Significance testing for small microarray experiments / Charles Kooperberg ... [et al.] — 9. Comparison of meta-analysis to combined analysis of a replicated microarray study / Darlene R. Goldstein ... [et al.] — 10. Alternative probe set definitions for combining microarray data across studies using different versions of Affymetrix oligonucleotide arrays / Jeffrey S. Morris ... [et al.] — 11. Gene ontology-based meta-analysis of genome-scale experiments / Chad A. Shaw — Pt. III. Combining Different Data Types — 12. Combining genomic data in human studies / Debashis Ghosh, Daniel Rhodes and Arul Chinnaiyan — 13. overview of statistical approaches for expression trait loci mapping / Christina Kendziorski and Meng Chen — 14. Incorporating GO annotation information in expression trait loci mapping / J. Blair Christian and Rudy Guerra — 15. misclassification model for inferring transcriptional regulatory networks / Ning Sun and Hongyu Zhao — 16. Data integration for the study of protein interactions / Fengzhu Sun ... [et al.] — 17. Gene trees, species trees, and species networks / Luay Nakhleh, Derek Ruths and Hideki Innan.