cit: hypothesis testing software for mediation analysis in genomic applications.
Bioinformatics
; 32(15): 2364-5, 2016 08 01.
Article
em En
| MEDLINE
| ID: mdl-27153715
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.
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Base de dados:
MEDLINE
Assunto principal:
Software
/
Genômica
Tipo de estudo:
Prognostic_studies
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article