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Statistical Applications in Biology and Genetics

Statistical Applications in Biology and Genetics. Tian Zheng Wednesday, March 12, 2003. Outline. Biological Background Overview of quantitative research area related to genetics Sample project I: Bayesian Regression Analysis with application to Microarray studies

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Statistical Applications in Biology and Genetics

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  1. Statistical Applications in Biology and Genetics Tian Zheng Wednesday, March 12, 2003

  2. Outline • Biological Background • Overview of quantitative research area related to genetics • Sample project I: Bayesian Regression Analysis with application to Microarray studies • Sample project II: BHTA algorithm for complex traits

  3. Chromosomes and genes • Video from the Human Genome Project • You can also find links to background readings at : http://www.stat.columbia.edu/~tzheng/research/statgen.html • Celebrating the 50th Anniversary of the discovery of DNA double-helix structure.

  4. Biology: Science of 21st century Everybody talks about it!

  5. Computational Biology (1) • Sequence to function • Sequence alignment using wet-lab results • Model aligned sequences • Predict function to sequence with unknown function using model fitted • Sequence to structure of proteins • Significance: sequence  structure  function

  6. Computational Biology (2) • Motif detection • Homology detection

  7. Bioinformatics/Genomics • Gene expression analysis (using DNA chips or Microarray) • Protein regulatory network inference • Pedigree inference • Phylogeny inference

  8. Genetic Epidemiology • Linkage mapping • Association mapping • Mapping for complex traits: quantitative traits, epistasis etc.

  9. Linkage and Association • Gene, alleles; • Haplotype • Transmission • Cross-over and recombination • Linkage

  10. Sample Project: Bayesian Regression Analysis • Mike West et al (2000) Bayesian Regression Analysis in the “large p, small n” Paradigm with application in DNA Microarray studies.

  11. What is a Microarray/DNA chip How Chips Work?

  12. Oligonucleotide Arrays Current “Golden Standard”!

  13. Affymetrix GeneChip System

  14. An Affymetrix GeneChip

  15. Gene Expression Data • n experiments (patients, types of cell lines, types of cancer tissues, etc) • p genes on one array • Subtracted and normalized gene expression data is a n by p matrix

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