FAMT
2.6Factor Analysis for Multiple Testing (FAMT) : Simultaneous Tests under Dependence in High-Dimensional Data
Overview
The method proposed in this package takes into account the impact of dependence on the multiple testing procedures for high-throughput data as proposed by Friguet et al. (2009). The common information shared by all the variables is modeled by a factor analysis structure. The number of factors considered in the model is chosen to reduce the false discoveries variance in multiple tests. The model parameters are estimated thanks to an EM algorithm. Adjusted tests statistics are derived, as well as the associated p-values. The proportion of true null hypotheses (an important parameter when controlling the false discovery rate) is also estimated from the FAMT model. Graphics are proposed to interpret and describe the factors.
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Code & Tests
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People & History
6 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- archivedRemoved from CRAN2025-11-02issues were not corrected despite reminders
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 2.62022-05-09 · diff ↗
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- RR 3.3.0 released · 2016-05-03
- RR 3.2.0 released · 2015-04-16
- RR 3.1.0 released · 2014-04-10
- 2.52013-09-30 · diff ↗
Package metadata
- Total releases
- 6
- License
- GPL (>= 2) OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 3.2 MB / 4 files
- Download size
- not tracked yet
- Installed size
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- With dependencies
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