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Using PBAT Capabilities Through SVS

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9.2 Using PBAT Capabilities Through SVS

SVS provides a graphical user interface (GUI) for the PBAT program, as well as the ability to import from and export to FBAT/PBAT- format and csv-format pedigree and phenotype files. PBAT genotypic and CNV data analysis capabilities are specifically supported by SVS using pedigree and phenotype spreadsheets within an SVS project. The PBAT capability is now current to v.3.6.1.

As mentioned above, PBAT tools support two scenarios: Pre-study and Post-study. In the Pre-study scenario, you can use the SVS PBAT capabilities for power calculations (see Pre-Study Power Calculation) to plan association studies (both family- and population-based) for virtually any given study design and ascertainment conditions.

The power of the statistic on a given study plan can be assessed to decide whether it has sufficient power. Alternatively, SVS allows you to easily (and repeatedly) change the design, the ascertainment conditions, the underlying genetic model or the mode of inheritance to find what parameters will give the study the best possible power.

For the Post-study scenario, the SVS PBAT analysis tools for genotypic and CNV data provide many useful capabilities for the statistical analysis of family-based association studies, e.g. simple FBAT or CNV FBAT statistics, multi-variate FBAT-statistics (FBAT-GEE and FBAT-PC for genotypic or CNV), FBAT-statistics for time-to-onset data, power estimations for the actually observed datasets, options to test linkage or association in the presence of linkage, options to use (bi- allelic or multi-allelic) marker or haplotype data, single or multiple traits (either separate traits or measurements recorded repeatedly over time) that may be quantitative, qualitative or time-to-onset, with nuclear families as well as extended pedigrees. Covariates and gene/covariate interactions in all computed FBAT statistics can easily be handled.

Statistical test results are returned in SVS spreadsheets. These spreadsheets allow you to find the most powerful test statistic and to reduce the large pool of traits and markers down to the most promising combinations in terms of the FBAT statistic.

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