Table of Contents
Bio 101: Genomics & Computational Biology
RNA1: Last week's take home lessons
RNA2: Today's story & goals
PPT Slide
(Whole genome) RNA quantitation objectives
Clustering vs. supervised learning
Cluster analysis of mRNA expression data
Cluster Analysis
Clustering hierarchical & non-
Clusters of Two-Dimensional Data
Key Terms in Cluster Analysis
Distance Measures: Minkowski Metric
Most Common Minkowski Metrics
An Example
Manhattan distance is called Hamming distance when all features are binary.
Similarity Measures: Correlation Coefficient
What kind of x and y give linear CC
Similarity Measures: Correlation Coefficient
Hierarchical Clustering Dendrograms
Hierarchical Clustering Techniques
The distance between two clusters is defined as the distance between
Single-Link Method
Complete-Link Method
Dendrograms
Which clustering methods do you suggest for the following two-dimensional data?
PPT Slide
PPT Slide
PPT Slide
Representation of expression data
Identifying prevalent expression patterns (gene clusters)
Cluster contents
PPT Slide
PPT Slide
RNA2: Today's story & goals
Motif-finding algorithms
Feasibility of a whole-genome motif search?
Sequence Search Space Reduction
Sequence Search Space Reduction
Motif Finding AlignACE (Aligns nucleic Acid Conserved Elements)
AlignACE Example Input Data Set
AlignACE Example The Target Motif
AlignACE Example Initial Seeding
AlignACE Example Sampling
AlignACE Example Continued Sampling
AlignACE Example Continued Sampling
AlignACE Example Column Sampling
AlignACE Example The Best Motif
AlignACE Example Masking (old way)
AlignACE Example Masking (new way)
MAP Score
MAP Score
AlignACE Example: Final Results
Indices used to evaluate motif significance
Searching for additional motif instances in the entire genome sequence
PPT Slide
PPT Slide
PPT Slide
Metrics of motif significance
Functional category enrichment odds
Functional category enrichment
Group Specificity Score (Sgroup)
Positional Bias
Comparisons of motifs
Clustering motifs by similarity
Palindromicity
S. cerevisiae AlignACE test set
Most specific motifs (ranked by Sgroup)
Most positionally biased motifs
Negative Controls
Positive Controls
Establishing regulatory connections
RNA2: Today's story & goals
|