It is increasingly common to combine Microarray and Quantitative Trait Loci data to aid the search for candidate genes responsible for phenotypic variation. Workflows provide a means of systematically processing these large datasets and also represent a framework for the re-use and the explicit declaration of experimental methods. Here we highlight the issues facing the manual analysis of microarray and QTL data for the discovery of candidate genes underlying complex phenotypes. We show how automated approaches provide a systematic means to investigate genotype-phenotype correlations. This methodology was applied to a use case of resistance to African trypanosomiasis in the mouse. Pathways represented in the results identified Daxx as one of the candidate genes within the Tir1 QTL region.

1. A Systematic approach to the Large-Scale Analysis of Genotype-Phenotype correlations Paul Fisher Dr. Robert Stevens Prof. Andrew Brass

4. Genotype to Phenotype

5. Genotype Phenotype ? Current Methods 200 What processes to investigate?

6. ? 200 Microarray + QTL Genes captured in microarray experiment and present in QTL ( Quantitative Trait Loci ) region Genotype Phenotype Metabolic pathways Phenotypic response investigated using microarray in form of expressed genes or evidence provided through QTL mapping

7. CHR QTL Gene A Gene B Pathway A Pathway B Pathway linked to phenotype – high priority Pathway not linked to phenotype – medium priority Pathway C Phenotype literature literature literature Gene C Pathway not linked to QTL – low priority Genotype

8. Issues with current approaches

9. Huge amounts of data 200+ Genes QTL region on chromosome Microarray 1000+ Genes How do I look at ALL the genes systematically?

11. Manual Methods of data analysis Navigating through hyperlinks No explicit methods Human error Tedious and repetitive

12. Implicit methods

15. Taverna Workflow Workbench http://taverna.sf.net

17. Pathway Resource QTL mapping study Microarray gene expression study Identify genes in QTL regions Identify differentially expressed genes Wet Lab Literature Annotate genes with biological pathways Annotate genes with biological pathways Select common biological pathways Hypothesis generation and verification Statistical analysis Genomic Resource

18. Replicated original chain of data analysis

19. Trypanosomiasis in Africa http://www.genomics.liv.ac.uk/tryps/trypsindex.html Andy Brass Steve Kemp + many Others

25. Pathway Resource QTL mapping study Microarray gene expression study Identify genes in QTL regions Identify differentially expressed genes Wet Lab Literature Annotate genes with biological pathways Annotate genes with biological pathways Select common biological pathways Hypothesis generation and verification Statistical analysis Genomic Resource

26. CHR QTL Gene A Gene B Pathway A Pathway B Pathway linked to phenotype – high priority Pathway not linked to phenotype – medium priority Pathway C Phenotype literature literature literature Gene C Pathway not linked to QTL – low priority Genotype DONE MANUALLY

30. Many thanks to: including: Joanne Pennock, EPSRC, OMII, myGrid, and lots more people