Reproducibility and concordance with alternative cell type quantification methods

Cell typeCorrelation with IHCRoot Mean Squared Error from IHCCorrelation with flowRoot Mean Squared Error from FlowMean pairwise similarity statistic in TCGASD due to technical noise (log2 scale)Proportion of variance due to noise
B-cells0.620.0640.590.130.0022
CD45cNA0.12490.0024
Cytotoxic cells0.690.08130.001
DC0.460.23070.0151
Exhausted CD80.440.16240.0062
Macrophages0.710.08280.0013
Mast cells0.740.19490.0086
Neutrophils0.480.190.0026
NK CD56dim cells0.470.0710.400.23470.1073
NK cells0.510.1180.470.19380.017
T-cells0.661.3a0.78a0.0640.810.11160.0021
Th1 cellscNA0.22120.0304
TregcNA0.3710.049
CD8 T cells0.531.50.780.1380.510.18420.0045
CD4 cellsb0.65b0.752

aUsed to normalize the other cell types; 0.78 and 0.064 are the highest correlation and lowest RMSE observed between gene expression and flow for any T-cells vs. other cell type contrast

bCalculated as the T-cell score minus the CD8 cell score

cOnly one marker gene; quality impossible to assess in expression data alone

Root mean squared errors are calculated from log2-scale abundance measurements. The mean pairwise similarity statistic measures how well a gene set’s co-expression pattern adheres to the co-expression pattern of ideal marker genes, with a value of 1 indicating perfect correlation with a slope of 1. The standard deviation (SD) and proportion of variance due to noise were calculated from triplicate gene expression assays from tumor sample RNA