Fig. 4: Application to mouse spermatogenesis dataset measured by Slide-seq. | Nature Communications

Fig. 4: Application to mouse spermatogenesis dataset measured by Slide-seq.

From: Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding

Fig. 4

a Visualization of the ground truth cell types using UMAP embedding. ES elongating spermatid, RS round spermatid, SPC spermatocyte, SPG spermatogonium. b Visualization of the Spatial-ID predictions using UMAP embedding. c The comparison of cell type annotation accuracy; n = 6 independent samples; Center line, median; box limits, upper and lower quartiles; whiskers, 1.5× interquartile range. d Spatial organization of the ground truth cell types of a wild-type sample, and the predictions of Spatial-ID and the control methods. Bar scale 400 µm. e Spatial organization of the ground truth cell types of an ob/ob sample, and the predictions of Spatial-ID and the control methods. Bar scale 400 µm. f The average time cost per sample of Spatial-ID and control methods in this mouse spermatogenesis dataset. The comprehensive results for all SRT datasets in this study can be found in Supplementary Table 3. g The running efficiency analysis. The left one shows the scheme of field view sampling. The right one shows that the runtime of Spatial-ID increases linearly as the number of cells increases. The regression plots of runtimes are presented as mean values with 95% confidence intervals.

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