bayefdr
Bayesian Estimation and Optimisation of Expected False Discovery Rate
Implements the Bayesian FDR control described by Newton et al. (2004), doi:10.1093/biostatistics/5.2.155. Allows optimisation and visualisation of expected error rates based on tail posterior probability tests. Based on code written by Catalina Vallejos for BASiCS, see Beyond comparisons of means: understanding changes in gene expression at the single-cell level Vallejos et al. (2016) doi:10.1186/s13059-016-0930-3.
- Version0.2.1
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Languageen-gb
- Last release10/26/2022
Documentation
Team
Alan O'Callaghan
Catalina Vallejos
Insights
Last 30 days
This package has been downloaded 259 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 11 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 3,345 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was May 08, 2024 with 33 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
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Dependencies
- Imports5 packages
- Suggests2 packages