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 i

SUBMITTER: Millstein J 

PROVIDER: S-EPMC4965632 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature