Workshop 1 (Part 2) - Department of Statistics - Purdue University Skip to main content

Statistical design of experiments and linear mixed models, and their applications in the context of bioinformatics

Speaker(s)

  • Bruce Craig (Purdue University)
  • Olga Vitek (Purdue University)

Description

The 2-day workshop discusses the use of linear and generalized linear models in design and analysis of experiments, and their applications in modern quantitative high-throughput biological investigations. The morning sessions focus on general aspects of design and analysis of experiments. They cover topics such as fixed effects and mixed effects linear models, analysis of incomplete block designs, analysis of repeated measures data, generalized linear mixed effects models and power determination. The sessions present extensive case studies, and examples of analysis using SAS. 

The afternoon sessions discuss the use and the extensions of linear and generalized linear modeling for high-throughput quantitative biological applications. The topics include Empirical Bayes linear mixed models for continuous response (e.g. gene expression microarrays and quantitative proteomics and metabolomics), and models for experiments with count response (e.g. RNA-seq and spectral counts proteomics). Additional related topics are normalization, methods to control False Discovery Rate, power determination with multiple tests, and differential expression of pre-defined sets of genes. The discussion is illustrated with case studies, and examples of analysis using R and Bioconductor. 

Schedule

Thur, June 21 - Location: STEW 202

TimeSpeakerTitle
8:30 - 9:55 Bruce Craig Generalized linear mixed effects models
10:30 - 11:55 Bruce Craig Generalized linear mixed effects models
12:00-1:30 PM Lunch
1:30 - 2:55 Olga Vitek Design and analysis of quantitative high-throughput experiments with a categorical response (e.g. RNA-seq; proteomics with spectral counts)
3:30 - 4:55 Olga Vitek Design and analysis of quantitative high-throughput experiments with a categorical response (e.g. RNA-seq; proteomics with spectral counts)

Purdue Department of Statistics, 150 N. University St, West Lafayette, IN 47907

Phone: (765) 494-6030, Fax: (765) 494-0558

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