Figure 4

Simulation study showing the performance of GRSN. Differential gene expression was simulated starting with a dataset containing 10 biological replicates. The simulation was repeated 100 times and each time the 10 samples were divided into two equal groups, gene expression was simulated in the second group, and a randomly generated, non-linear artifact (skew) was applied to each sample. In each simulation, GRSN was applied to correct the simulated skew. A. First row – sample 8 of 10 from simulation 100 of 100. Left hand panel shows M vs. A plot before simulated skew. Second panel from left shows the introduction of simulated skew. Third panel from left shows GRiS and calibration curve from GRSN process. Right hand panel shows data after GRSN correction of simulated skew. Second row – same as first row, but for simulation 81 of 100. B. GRSN improves gene selection results. Left panel shows true positive gene selection results for simulated up and down genes as indicated before simulated skew is added, after simulated skew is added, and after GRSN is used to correct the simulated skew. Critical portions of the y-axis scale are expanded at the top and bottom of the graph. Middle panel shows false negatives with the bottom portion of the y-axis scale expanded at the bottom. Right panel shows false positive results. Data is represented using standard Tukey box plots. C. Average Fold Change (FC) variation. The average FC for each simulated FC value is plotted showing the variation over all simulated genes and 100 simulations. The left third of the graph shows values for simulated data before skew is introduced, the middle third shows values with skew added, and the right third shows values after GRSN correction of skew as indicated. Box plots are shown.