Fig. 3
From: Effective methods for bulk RNA-seq deconvolution using scnRNA-seq transcriptomes
The accuracy of cell-mixture deconvolution. A The impact of RNA-seq and scRNA-seq normalization strategies and the choice of deconvolution methods on deconvolution accuracy, as assessed by Pearson correlation and root mean square error (RMSE); darker and larger circles represent higher Pearson and lower RMSE values, respectively. B Deconvolution results for the normalization strategy with the lowest RMSE; axes are in log10 scales. Each scatterplot contains 36 data points corresponding to 6 cell lines in 6 mixtures, with gold standard abundance estimates based on cell counts and predicted abundances based on deconvolution