cit: hypothesis testing software for mediation analysis in genomic applications.

ABSTRACT

MOTIVATION The challenges of successfully applying causal inference methods include (i) satisfying underlying assumptions, (ii) limitations in data/models accommodated by the software and (iii) low power of common multiple testing approaches. RESULTS: The causal inference test (CIT) is based on hypothesis testing rather than estimation, allowing the testable assumptions to be evaluated in the determination of statistical significance. A user-friendly software package provides P-values and optionally permutation-based FDR estimates (q-values) for potential mediators. It can handle single and multiple binary and continuous instrumental variables, binary or continuous outcome variables and adjustment covariates. Also, the permutation-based FDR option provides a non-parametric implementation. CONCLUSION: Simulation studies demonstrate the validity of the cit package and show a substantial advantage of permutation-based FDR over other common multiple testing strategies. AVAILABILITY AND IMPLEMENTATION The cit open-source R package is freely available from the CRAN website (https//cran.r-project.org/web/packages/cit/index.html) with embedded C ++ code that utilizes the GNU Scientific Library, also freely available (http//www.gnu.org/software/gsl/). CONTACT joshua.millstein@usc.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.