Application and Analysis of Microarrays BME 210, Winter 2004 Syllabus

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Tentative Syllabus

• Overview and Background (Lowe), Tue Jan 6 [pdf]
• Basics of gene expression
• Vocabulary
• Introduction to functional genomics
• The miracle of microarrays (Lowe), Thu Jan 8 [pdf]
• Types of arrays (oligo vs. PCR)
• Types of experiments (cancer, cell-cycle, etc)
• Types of analyses (Type I and Type II)
• Challenges and future promises
• Spotted array design (Lowe), Tue Jan 13 [pdf]
• Spotted array construction
• Feature design
• Building a robot
• Slide and DNA sample preparation
• Post-processing
• Crossing the digital divide (Stuart), Thu Jan 15 [pdf]
• Scanning images
• Data representation
• Relational structure
• Storing and exchanging data
• Public repositories
• Designing microarray experiments (Stuart & Lowe), Tue Jan 20
• Statistical design (Stuart) [pdf]
• Variance, bias, power
• Replication and reference structure (reference graphs)
• Correlation and dependence
• Applied design (Lowe) [pdf]
• Time-oriented data
• Comparing genetic backgrounds and developmental stages
• Classifying cancer
• Comparing different genomes
• Mapping small nucleotide polymorphisms in human
• Spike controls
• Lab 1: Introduction to GenePix, Thu Jan 22 [html]
• Gridding
• Loading and extracting data
• Using a print-list
• Normalization & Quality Assurance (Lowe & Stuart), Tue Jan 27
• Experimental approaches to QA (Lowe) [pdf]
• Minimizing and handling artifacts
• Auto and manual flagging
• Validating intensities
• Common biases (e.g. dye)
• Computational normalization (Stuart) [pdf]
• MA-plots
• Loess normalization
• Formalizing error with linear models
• Lab 2: Bioconductor, Thu Jan 29 [html]
• Introduction to R and Bioconductor
• Boxplots, MA-plots, loess normalization
• Lab 2 (redo): Bioconductor (redo) and normalization, Tue Feb 3 [html]
• Since nothing worked on the 29^th, we had to redo the lab...
• Lab 3: Identify cold shock responsive genes in Archae, Thu Feb 5 [html]
• Detect differential expression between a control and experimental condition
• t-test
• Analyzing an experiment series (Josh), Tue Feb 10 [pdf]
• Detecting differentially expressed genes
• Parametric tests (t-test and ANOVA)
• Non-parametric tests (Wilcoxon, Ranks, Permutation)
• Introduction to clustering
• Proximity measures
• Lab 4: Identify stress-response genes in Archae, Thu Feb 12 [html]
• Detect differential expression across various stress conditions.
• ANOVA
• Permutation test
• Introduction to cluster analysis (k-means)
• Inferring regulatory networks (Lowe), Tue Feb 17
• Enrichment of cis-regulatory motifs in clusters
• Finding overrepresented words in promoter regions
• Inferring operon structure
• Lab 5: cis-regulatory motif discovery, Thu Feb 19 [html]
• Use BioProspector to identify putative motifs in archae stress clusters
• Genome-Mean expression profiles
• Clustering and cluster evaluation (Stuart), Tue Feb 24 [pdf]
• Agglomerative: HCA
• Derisive: K-means, SOMs
• Probabilistic clustering: Bayesian networks
• Intrinsic measures: (Within-vs-between variance, Jaacard Index, Rand Index, figure of merit, cross-validation)
• Extrinsic measures (comparison to positive & negative controls)
• Gold standards (Gene Ontology, KEGG, MIPS)
• Analyzing enrichment of functional groups with the hypergeometric distribution
• Cluster robustness
• The Bootstrap
• The Gap statistic
• Lab 6: Cluster evaluation, Thu Feb 26 [html]
• Derive series of clustering solutions from bootstrapped data
• Measure degree of co-clustering
• Measure enrichment of KEGG functional categories
• Classifying gene expression – supervised learning (Stuart), Tue Mar 2 [pdf]
• k-Nearest-Neighbors
• Support Vector Machines
• Lab 7: supervised learning, Thu Mar 4 [html]
• Advanced topics I (Stuart), Tue Mar 9 [pdf]
• Two-way clustering (context-sensitive search for coherent modules)
• Recommender systems for finding genes involved in known pathways
• Probabilistic Methods (Bayesian Networks and Probabilistic Relational Models)
• Advanced topics II (Lowe), Thu Mar 11
• Single-cell expression profiling
• Functional arrays
• Tissue arrays
• Protein arrays

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