Statistical Bioinformatics
Statistics 5570/6820, Spring 2009
Instructor: John R. Stevens

Course Documents and Announcements

• Course Announcement
• Course Syllabus
• GSE 5245 data --- ace format --- zip format
• Homework 1
• Homework 2
• Lies
• Homework 3
• Project --- sample 1 --- sample 2 --- sample 3 --- sample 4
• Homework 4
• Homework 5 --- hw5.fasta
• Final Exam

Unit 1: Gene Expression Analysis - Technology and Preprocessing

• Notes 1.1 --- Introduction to Microarray Technology
• Notes 1.2 --- Install and Use R
• Notes 1.3 --- Images to Useful Data
• Notes 1.4 --- Preprocessing and MAS5
• Notes 1.5 --- RMA / GCRMA Preprocessing
• Notes 1.6 --- PLIER Preprocessing

Unit 2: Gene Expression Analysis - Visualization

• Notes 2.1 --- Quality Checks
• Notes 2.2 --- Distances
• Notes 2.3 --- Clustering
• Notes 2.4 --- Visualization

Unit 3: Gene Expression Analysis - Inference

• Notes 3.1 --- Multiple Hypothesis Testing
• Notes 3.2 --- Filtering
• Notes 3.3 --- Tests for Differential Expression
• Notes 3.4 --- Random Forests

Unit 4: Gene Expression Analysis - Annotation

• Notes 4.1 --- GO and KEGG Annotation
• Notes 4.2 --- Interactive Report Files
• Notes 4.3 --- Gene Set Testing
• Notes 4.4 --- Global Testing and Graphs

Unit 5: Mass Spectrometry Analysis - Technology and Preprocessing

• Notes 5.1 --- Recent Tools for Preprocessing

Unit 6: Sequence Analysis

• Notes 6.1 --- Introduction to Pairwise Alignment
• Notes 6.2 --- Introduction to BLAST
• Notes 6.3 --- Introduction to Multiple Alignment

6570 Presentations

• Ensemble Methods --- 4/17/09
• Time-Course --- 4/22/09
• Multiple Testing --- 4/24/09

Miscellaneous

• Good microarray review articles:
  • Lockhart paper: a good review of technology
  • Schwender article: a good review of terminology and "big picture"
  • Craig paper: a good review of design and application issues
• Good R resources:
  • R: The R Project
  • CRAN: The Comprehensive R Archive Network
  • Introduction to R: A good resource for most uses of R
  • Bioconductor Project: Free R packages for the analysis of genomic data
  • R reference card: Tom Short's ''cheat sheet'' for R commands
• Good journals to watch:
  • Bioinformatics
  • BMC Bioinformatics
  • Biometrics
  • BMC Genomics
  • Genome Biology
  • Nature
  • Nature Genetics
  • Comparative and Functional Genomics
  • Nucleic Acids Research