1. ClueGene: An Online Search Engine for Querying Gene Regulation
David M. Ng
2008 January 16

2. System Overview
Every operation generates a “working set” that can be modified and used as the query in the next search iteration
Common structure for all search and test operations with no dead ends

4. New Features Coexpression test Dataset ranking and heat map
Heat map for expression data

5. Coexpression Test
Coexpression search performed using half of the working set selected at random
AUC computed based on finding the held-out half of the working set
Coexpression test score is the average of ten such searches
Test score displayed in the context of representative pathways with scores computed the same way as a “thermometer”
Precision-recall curves are also displayed

6. Dataset Ranking and Heat Map
Datasets are ranked by their contribution to the scores of the working set genes
Display as a heat map
Future work: allow user to provide dataset feedback

7. Expression Data Heatmap
Displays the expression data for a dataset
For the following genes
Result genes
Query genes
Contrast genes
Randomly selected non-query and non-result genes
Same number as number of result genes

8. Expression Data Heat Map Script
Generate a heat map as a Web page for specified query, result, and contrast genes for a given dataset.
Usage:
Invoke as a URL:
Specify parameters following a ?
Parameters are name-value pairs separated by ampersands

9. Expression Data Heat Map Script Parameters
species=<species code>
ds=<dataset name>
transactionId=<transaction id>
<result gene id>=resultGene
<query gene id>=queryGene
<contrast gene id>=contrastGene

10. Expression Data Heat Map Example
ds=Segal03&species=sce&transactionId= &
YJR123W=resultGene&YLR340W=resultGene&YNL301C=resultGene&
YJR123W=queryGene&YLR340W=queryGene&YBL072C=queryGene&
YNL232W=contrastGene&YDL175C=contrastGene&YDL104C=contrastGene

11. Invoking ClueGene via URL
ClueGene provides a GET interface

12. Future Work
Dataset selection
Reimplement
Set-based user model

13. Reimplement ClueGene Current ClueGene Hard to maintain
10,000+ lines of Perl in 20 files
800+ lines of HTML and JavaScript
Hard to maintain
Old CGI technology

14. Set-Based User Model
Generalization of Greg’s Gene Sets and Gene Set Families
Set members can be atomic or sets
Set members have attributes
Intrinsic to the element
Dependent on the set under consideration
Issue: combining duplicate attributes

15. Benefits of Set Model
A single, consistent model for all aspects of gene search engines
Easier understanding of inputs, operations, and results
More straightforward user interface implementation
More general manipulation of sets supports
saving/loading of sets
combining result sets via set operations such as intersection and union

16. ClueGene Sets Gene: atom Cluster: set of genes
Attributes such as unique id, display name, aliases
Cluster: set of genes
Dataset: set of cluster sets
Cluster compendium: set of dataset sets
Query set: set of genes
Expected set: set of genes

17. ClueGene Query Inputs Output Computing AUC Cluster compendium set
Query set
Output
Set of all genes in the genome
Set-specific attributes for rank and score
Computing AUC
Additional input: expected set
Result AUC: attribute of result set

18. Other Operations Known and Novel Motif Search GO Category Search
Input: Working set
Output: Set of {set for each result motif containing the genes with the motif}
GO Category Search

19. Clustering Expression data: set of genes Clustering
Set-specific attributes for expression data for each gene
Clustering
Input expression data: set of genes of expression data
Output dataset: set of cluster sets
Issue: handling operations that take a really long time