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Fig. 6 | Genome Biology

Fig. 6

From: SRTsim: spatial pattern preserving simulations for spatially resolved transcriptomics

Fig. 6

Benchmarking spatial expression analysis methods using synthetic data from SRTsim. Synthetic data are either generated based on the DLPFC reference (A–D) or the STARmap reference (E–H). A A representative gene in the DLPFC reference data (sample 151673) displays a random spatial expression pattern. B Representative genes in the DLPFC reference data display four distinct spatial expression patterns corresponding to four different layered structures (Layer1, Layer 2, Layer 3, and WM, respectively). C Quantile–quantile plot of the observed −log10(P) from different methods against the expected −log10(P) under the null SRTsim simulations based on the DLPFC reference. P values were combined across ten simulation replicates. D Power plots show the proportion of true positives (y-axis) detected by different methods at a range of FDRs (x-axis) for the alternative SRT simulations based on the DLPFC reference. Each panel corresponds to the spatial expression pattern displayed in B. SE strength is set to be five-fold. E A representative gene in the STARmap reference data displays a random spatial expression pattern. F Representative genes in the STARmap reference data display four distinct spatial expression patterns that correspond to four different layered structures (Layer2/3, Layer 4, Layer 5, and Layer 6, respectively). G Quantile–quantile plot of the observed −log10(P) from different methods against the expected −log10(P) under the null SRTsim simulations based on the STARmap reference. P values were combined across ten simulation replicates. H Power plots show the proportion of true positives (y-axis) detected by different methods at a range of FDRs (x-axis) for the alternative SRT simulations based on the STARmap reference. Each panel corresponds to the spatial expression pattern displayed in F. SE strength is set to be three-fold

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