Sample size calculation is a crucial step in study design but is not yet fully established for RNA sequencing (RNA-seq) analyses. To evaluate feasibility and provide guidance, researchers from the Johannes Gutenberg University Mainz evaluated RNA-seq sample size tools identified from a systematic search. The focus was on whether real pilot data would be needed for reliable results and on identifying tools that would perform well in scenarios with different levels of biological heterogeneity and fold changes (FCs) between conditions.
- RNASeqPower – https://bioconductor.org/packages/release/bioc/html/RNASeqPower.html
- RSPS – https://rdrr.io/cran/RSPS/
- RNASeqPowerCalculator – http://www2.hawaii.edu/~lgarmire/RNASeqPowerCalculator.htm
- PROPER – https://www.bioconductor.org/packages/release/bioc/html/PROPER.html
- Scotty – http://scotty.genetics.utah.edu/
- ssizeRNA – https://rdrr.io/cran/ssizeRNA/man/ssizeRNA_vary.html
- RnaSeqSampleSize – https://cqs.mc.vanderbilt.edu/shiny/RnaSeqSampleSize/
- SSPA – https://www.bioconductor.org/packages/release/bioc/html/SSPA.html
The researchers used simulations based on real data for tool evaluation. In all settings, the six evaluated tools provided widely different answers, which were strongly affected by FC. Although all tools failed for small FCs, some tools can at least be recommended when closely matching pilot data are available and relatively large FCs are anticipated.
Schematic of sample size calculation
Parameters are estimated from pilot data or publicly available data either by the tool or the user. Sample size estimation is either performed via simulation or by using formulas. The tool position reflects the starting point of the calculation.