for Identifying Sequence Variations That Correlate with Virus Phenotypic Characteristics in the Virus Pathogen Resource ViPR July 22 2013 MetaCATS Overview Overview of the MetaCATS algorithm ID: 474427
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Statistical Tool for Identifying Sequence Variations That Correlate with Virus Phenotypic Characteristics in the Virus Pathogen Resource (ViPR)July 22, 2013
Meta-CATSSlide2
OverviewOverview of the Meta-CATS algorithmMetadata groupingStatistical testingTwo similar integrated web toolkits :The Virus Pathogen Resource (ViPR – viprbrc.org)The Influenza Research Database (IRD – fludb.org)Review results from two use casesSlide3
The Meta-CATS AlgorithmCollect a set of virus strains(search database or upload file)Group strains by a metadata attribute or upload a spreadsheet that defines the groupsPerform multiple sequence alignmentAutomatically identify residue positions where there are
statistically significant differences
between the groupsReport results
A flexible web-based tool with a few basic steps: Slide4
Grouping based on MetadataExamples of metadata that may be of interest:Host of isolationSeverity of diseaseDrug resistanceGeographical locationDate of isolationPhylogenetic clade assignmentOther taxonomic assignments (serotype, genotype, etc.)Or any User Defined attribute in a spreadsheetSlide5
The Meta-CATS ComputationMultiple sequence alignment of all strainsAt each residue position (nucleotide or AA) perform a chi-squared test of independenceWhen 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.Slide6
The ViPR / IRD ToolkitsLocation of new Meta-CATS AlgorithmSlide7
Workbench and Metadata AttributesSlide8
First use Case: SARS CoronavirusThe “Host” metadata field was used to find the positional differences in Human and Civet predominant strainsThe 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) 3209-26Slide9
Second Use Case: Dengue VirusThe “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 serotypesThe 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)Slide10
SummaryThrough 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.
www.viprbrc.org
www.fludb.org
ViPR
IRDSlide11
AcknowledgementsJ Craig Venter InstituteRichard H. ScheuermannBrett E. PickettBrian AevermannYun ZhangRick StantonSMUMengya LiuEva SadatMonnie McGee
Northrop Grumman
Health Solutions
Edward B. KlemSherry HeSam ZarembaSanjeev KumarLiwei ZhouWei JenVecnaChristopher N. Larsen