| AI | Artificial intelligence |
| AMD | Age-related macular degeneration |
| AUCs | Areas Under the Curve |
| BaySeq | Bayesian Sequencing |
| CIBERSORT | Cell type Identification By Estimating Relative Subsets Of RNA Transcripts |
| DAVID | Database for Annotation, Visualization, and Integrated Discovery |
| DEGs | Differentially expressed genes |
| DESeq2 | Differential Expression analysis based on the Negative Binomial distribution (version 2) |
| DL | Deep learning |
| DME | Diabetic macular edema |
| DNN | Deep neural networks |
| DR | Diabetic retinopathy |
| DS-NMF | Deep Subspace Nonnegative Matrix Factorization |
| ECM | Extracellular matrix |
| edgeR | Empirical Analysis of Digital Gene Expression Data in R |
| GO | Gene Ontology |
| GSEA | Gene Set Enrichment Analysis |
| GSVA | Gene Set Variation Analysis |
| GWAS | Genome-Wide Association Study Analysis |
| iPSC | Induced pluripotent stem cells |
| KCS | Keratoconjunctivitis sicca |
| LASSO | Least absolute shrinkage and selection operator |
| LIGER | Linked Inference of Genomic Experimental Relationships |
| LIME | Local Interpretable Model–Agnostic Explanations |
| limma | Linear Models for Microarray Data |
| MAGIC | Markov Affinity-based Graph Imputation of Cells |
| MCODE | Molecular Complex Detection |
| ML | Machine learning |
| NMF | Negative matrix factorization |
| NPDR | Non-proliferative diabetic retinopathy |
| OCT | Optical coherence tomography |
| PCA | Principal component analysis |
| PDMS | Polydimethylsiloxane |
| PDR | Proliferative diabetic retinopathy |
| POAG | Primary open-angle glaucoma |
| PVR | Proliferative vitreoretinopathy |
| QBAM | Quantitative brightfield absorbance microscopy |
| RF | Random forest |
| RGCs | Retinal ganglion cells |
| RNA-seq | RNA sequencing |
| RPE | Retinal pigment epithelium |
| SCCAF | Single-Cell Clustering Assessment Framework |
| ScGPS | Single-Cell Global fate Potential of Subpopulations |
| ScRNA-seq | Single-cell RNA sequencing |
| scVI | Single-cell variational inference |
| SHAP | SHapley Additive exPlanations |
| SVM | Support vector machine |
| TED | Thyroid eye disease |
| TEMPO | Tracing Expression of Multiple Protein Origins |
| TNF | Tumor Necrosis Factor |
| t-SNE | t-distributed Stochastic Neighbor Embedding |
| UMAP | Uniform Manifold Approximation and Projection |
| VAE | Variational autoencoders |
| VEGF | Vascular endothelial growth factor |
| v-SVR | Support vector regression (SVR) |
| WGCNA | Weighted gene co-expression network analysis |
| XGBoost | eXtreme Gradient Boosting |