1. Galaxy: Integrative, Reproducible Analysis of Genomics Data Genomic and Proteomic Approaches to Heart, Lung, Blood and Sleep Disorders Jackson Laboratories Ross Hardison September 10, 2008 Galaxy is developed and maintained by Anton Nekrutenko (PSU) and James Taylor (Emory U)

2. Types of data in genomics Sequences Comparisons of DNA and protein sequences Expression data Chromosomes and chromatin data Experimental manipulation Variation and phenotypes Protein structure and function Stored in databases and browsers (e.g. UCSC Genome Browser) Many analysis tools (Galaxy)

3. Some major web resources in genomics UCSC Genome Browser and Table Browser –http://genome.ucsc.edu/ Ensembl and EnsMart/BioMart –http://www.ensembl.org/ TIGR Comprehensive Microbial Resource –http://cmr.tigr.org/ NCBI for Blast server, PubMed, Gene Expression Omnibus, dbSNP, etc. –http://www.ncbi.nlm.nih.gov/ dCode for alignments and other –http://dcode.org HapMap for haplotype and variation –http://hapmap.org Galaxy for data retrieval and analysis –http://galaxy.psu.edu

4. Sequences DNA sequences –Whole genomes and chromosomes –Genes Transcripts –Protein-coding and noncoding transcripts –Full-length or partial (expressed sequence tags or ESTs) Protein sequences –Known –Predicted Repeats Variants

5. Sequences from CFTR: Browser view

6. Regulation-related features around T2D risk variants Reg Pot

7. Browsers vs Data Retrieval Browsers are designed to show selected information on one locus or region at a time. –UCSC Genome Browser –Ensembl Run on top of databases that record vast amounts of information. Sometimes need to retrieve one type of information for many genomics intervals or genome-wide. Access this by querying on the tables in the databases or “data marts” –UCSC Table Browser –EnsMart or BioMart

8. Retrieve all the protein-coding exons in humans

9. Challenges in genomic data analysis We have great browsers and data warehouses –But most lack facilities for performing sophisticated analysis Many useful computational tools have been developed in bioinformatics –But they are not well integrated, they have different user interfaces, different data formats, etc.

10. Some common solutions Glue it all together with Excel –Until you realize Excel cannot handle that much data and the match isn’t coming out right anyway… Glue it all together with Perl –But that leads to duplication of effort, duplication of bugs, ….

11. A better solution Build a framework that: –Defines a common format for describing the interfaces of different computational tools and databases –Provides the infrastructure to adapt those interfaces into standard form –Defines common data types and standards for integrating the results

13. Two faces of Galaxy A web site where you can easily perform complex analysis integrating various data sources and computational tools A framework to easily build similar sites that integrate your choice of tools and data sources

14. Galaxy: Data retrieval and analysis Flexible data retrieval –From multiple external sources –Upload from user’s computer –Upload as URL from any site Hundreds of computational tools –Data editing, filter, sort –File format conversion –Extract sequences and alignments –Operations: merge, intersection, complement, cluster … –Get conservation and other scores for intervals –Statistics –Graphs and displays –EMBOSS tools for sequence analysis –HyPhy tools for molecular evolutionary analysis Workflows: run multiple steps reproducibly

15. Welcome to Galaxy Welcome screen, changes periodically News When tools are invoked, displays information on the tool and allows user to chose parameters

16. Tool choice Titles are toggles; more options are displayed when you click on them

17. History Titles are toggles; more information is displayed when you click on them Click on the “eye” to see all the data on another page Click on the “pencil” to edit the attributes Click on the “x” to delete “Refresh” to get results if they have not appeared or to get status of query Use “options” next to “History” to save, rename, move to or share histories. Must be logged in to do this.

18. Proxy based tools (e.g. UCSC Table Browser) User makes request to Galaxy Galaxy delegates request to external site

19. Proxy based tools External site generates response - If data, Galaxy determines data type, processes it and adds it to the history - Otherwise, response is returned to user

20. Command line tools Pick one of the programs from the left “Tools” bar

21. User chooses parameters for tool

22. Command is run

23. Background jobs in Galaxy

24. Web page with datasets on transcriptional regulation

25. Data uploads to Galaxy: use the URL

26. How many DHS overlap with high RP intervals?

27. Overlaps of DHS with high RP segments (25%) and highly constrained segments (43%) 24,330/95,709 = 0.254 41,000/95,709 = 0.428

28. Get constraint scores for intervals

29. Histogram of phastCons scores

30. Mean vs Maximum phastCons Distribution of phastCons scores in DHS that are also occupied by CTCF mean max n=7000

31. Many thanks … James Taylor, Anton Nekrutenko, Funding from NIDDK, NHGRI, Huck Institutes of Life Sciences at PSU Yong Cheng, Demesew Abebe, Christine Dorman, …, Ying Zhang, David King, Swathi Ashok Kumar