cit
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DescriptionHypothesis testing software for mediation analysis in genomic applications
Homepagehttp://www.gnu.org/software/gsl/
Publications
cit: hypothesis testing software for mediation analysis in genomic applications
Joshua Millstein; Gary K. Chen; Carrie V. Breton
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.
DOI: https://doi.org/10.1093/bioinformatics/btw135
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3
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