Summarise the results of diffSCEs. Calculates the Median Absolute Deviation (MAD), Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) for the various properties and ranks them.

summariseDiff(diff)

Arguments

diff

Output from diffSCEs

Value

data.frame with MADs, MAEs, RMSEs, scaled statistics and ranks

Examples

sim1 <- splatSimulate(nGenes = 1000, batchCells = 20)
#> Getting parameters...
#> Creating simulation object...
#> Simulating library sizes...
#> Simulating gene means...
#> Simulating BCV...
#> Simulating counts..
#> Simulating dropout (if needed)...
#> Done!
sim2 <- simpleSimulate(nGenes = 1000, nCells = 20)
#> Simulating means...
#> Simulating counts...
#> Creating final dataset...
difference <- diffSCEs(list(Splat = sim1, Simple = sim2), ref = "Simple")
#> Note that the names of some metrics have changed, see 'Renamed metrics' in ?calculateQCMetrics. #> Old names are currently maintained for back-compatibility, but may be removed in future releases.
#> Note that the names of some metrics have changed, see 'Renamed metrics' in ?calculateQCMetrics. #> Old names are currently maintained for back-compatibility, but may be removed in future releases.
summary <- summariseDiff(difference) head(summary)
#> Dataset Statistic MAD MADScaled MADRank MAE MAEScaled #> 1 Splat Mean 3.545552e+00 NaN 1 3.129809e+00 NaN #> 2 Splat Variance 7.591704e-02 NaN 1 1.200872e-01 NaN #> 3 Splat ZerosGene 3.500000e+01 NaN 1 4.185500e+01 NaN #> 4 Splat MeanVar 4.092154e-01 NaN 1 4.692433e-01 NaN #> 5 Splat MeanZeros 4.500000e+01 NaN 1 4.415500e+01 NaN #> 6 Splat LibSize 6.258000e+04 NaN 1 6.246590e+04 NaN #> MAERank RMSE RMSEScaled RMSERank #> 1 1 3.498988e+00 NaN 1 #> 2 1 1.702264e-01 NaN 1 #> 3 1 4.627229e+01 NaN 1 #> 4 1 5.756617e-01 NaN 1 #> 5 1 5.414541e+01 NaN 1 #> 6 1 6.399102e+04 NaN 1