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Meta-CATS

Meta-CATS. Statistical Tool for Identifying Sequence Variations That Correlate with Virus Phenotypic Characteristics in the Virus Pathogen Resource (ViPR) July 22, 2013. Overview. Overview of the Meta-CATS algorithm Metadata g rouping Statistical testing

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Meta-CATS

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  1. Meta-CATS Statistical Tool for Identifying Sequence Variations That Correlate with Virus Phenotypic Characteristics in the Virus Pathogen Resource (ViPR) July 22, 2013

  2. Overview • Overview of the Meta-CATS algorithm • Metadata grouping • Statistical testing • Two similar integrated web toolkits : • The Virus Pathogen Resource (ViPR – viprbrc.org) • The Influenza Research Database (IRD – fludb.org) • Review results from two use cases

  3. The Meta-CATS Algorithm A flexible web-based tool with a few basic steps: • Collect a set of virus strains(search database or upload file) • Group strains by a metadata attribute or upload a spreadsheet that defines the groups • Perform multiple sequence alignment • Automatically identify residue positions where there are statistically significant differences between the groups • Report results

  4. Grouping based on Metadata Examples of metadata that may be of interest: • Host of isolation • Severity of disease • Drug resistance • Geographical location • Date of isolation • Phylogenetic clade assignment • Other taxonomic assignments (serotype, genotype, etc.) • Or any User Definedattribute in a spreadsheet

  5. The Meta-CATS Computation • Multiple sequence alignment of all strains • At each residue position (nucleotide or AA) perform a chi-squared test of independence • When there are more than 2 groups, at each position identified, perform a chi-square test to determine which pairs of groups contribute to the significant result. • Computed results can be viewed directly or downloaded as a CSV file.

  6. The ViPR / IRD Toolkits Location of new Meta-CATS Algorithm

  7. Workbench and Metadata Attributes

  8. First use Case: SARS Coronavirus The “Host” metadata field was used to find the positional differences in Human and Civet predominant strains The Meta-CATS algorithm identified 117 nucleotide positions that significantly differed between the civet and human isolates. The raw p-values ranged from 2.49x10-2 to 4.33x10-12. “Virus Pathogen Database and Analysis Resource (ViPR): A Comprehensive Bioinformatics Database and Analysis Resource for the Coronavirus Research Community”. Picket et. al., Viruses. 2012 Nov 19;4(11) 3209-26

  9. Second Use Case: Dengue Virus • The “Geographic Location” metadata was used to identify 61 significant differences in the polyprotein between strains of Dengue-3 virus isolated from the Eastern Hemisphere and Western Hemisphere. • Further inspection of the group-specific amino acid composition found a clade of “outlier” sequences likely due to an international transmission event. • A separate analysis identified distinct NS1 amino acid residue variations correlating with DENV serotypes • The Meta-CATS algorithm identified 19 positions where the 4 serotypes differed. In 3 locations, which are located within experimentally-determined antibody epitopes, the p-values were less than 7.07x10-193. “Metadata-driven Comparative Analysis Tool for Sequences (meta-CATS): an Automated Process for Identifying Significant Sequence Variations Dependent on Differences in Viral Metadata.” Picket et. al., J. of Virology. (submitted)

  10. Summary Through the readily accessible search interface and integrated comparative genomics tools such as Meta-CATS, researchers can easily generate hypotheses that can then be tested in the lab and applied to the development of therapeutics and vaccines. IRD ViPR www.viprbrc.org www.fludb.org

  11. Acknowledgements J Craig Venter Institute • Richard H. Scheuermann • Brett E. Pickett • Brian Aevermann • Yun Zhang • Rick Stanton SMU • MengyaLiu • Eva Sadat • Monnie McGee Northrop GrummanHealth Solutions • Edward B. Klem • Sherry He • Sam Zaremba • Sanjeev Kumar • Liwei Zhou • Wei Jen Vecna • Christopher N. Larsen

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