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. 2020 Aug 17;16(8):e1008120. doi: 10.1371/journal.pcbi.1008120

Fig 2. Computational estimation of cell-type proportions.

Fig 2

(A) Figure shows the Spearman correlation coefficient between IHC-based cell-type estimates and four deconvolution algorithms, in addition to the “single marker” based approach. For the single marker based approach, we used the expression of the widely used marker genes: ENO2 for neurons, GFAP for astrocytes, CD68 for microglia, CD34 for endothelial, OLIG2 for oligodendrocytes. Correlations larger than 0.2 provide evidence that the gene expression cell-type proportion estimate for that cell-type are correlated with the IHC cell-type proportion using an unadjusted p-value threshold of 0.05. (B) Estimates of absolute proportions of each cell-type in the DLPFC according to the four algorithms tested, and IHC (experimentally measured in this study). Box plots depict the range of proportions across 70 individuals. (C) Boxplots depict the similarities and differences of predicted cell-type proportions (using DSA algorithm and Zhang markers) across nine brain regions, based on bulk GTEx tissue data.