Figure 2.
Quality control metrics and normalization performance of GeoMx spatial transcriptomic data. (A) Workflow illustrates data normalization. Q3 normalization was selected for downstream analysis because it provided consistent performance across heterogeneous retinal layers compared to negative probe and housekeeping normalization. (B) Sequencing saturation for each ROI. (C) Number of genes expressed above LOQ2 (second limit of quantitation, calculated as geometric mean × geometric standard deviation2 of negative probes) across all the retinal cells, illustrating expression detection breadth. (D) Signal-to-noise ratio (=counts/LOQ) distribution by sample type, reflecting assay sensitivity and specificity across ROIs. (E) Principal component analysis demonstrated moderate clustering by sample group, highlighting notable differences between the molecular profiles of control and post-COVID-19 samples, despite some within-group variance. (F) Pearson correlation analysis of central and peripheral control RPE ROIs, labeled by donor identifier (ID), demonstrates conserved RPE transcriptomic profiles across retinal regions. Scale reflects the full range of observed values. Self-correlation values (r = 1.0) are shown for reference but were excluded from interpretation of regional conservation analyses, as they do not provide biologically informative comparisons. AOI = area of illumination; COVID-19 = coronavirus disease 2019; IPL = inner plexiform layer; OPL = outer plexiform layer; ROI = region of interest; RPE = retinal pigment epithelium; PCA = principal component analysis; QC = quality control.