Provided by Liang Li and Lulu Shang.
If you need further assistance, contact TBEL-CDMC@mdanderson.org.
Task | Approach | Tools | Applications |
 | Quality control | SpotClean | Quality control of spatial transcriptomics data, removing ambient RNA contamination. |
 | Batch effect removal | Harmony, ComBat, BBKNN | Correcting batch effects across datasets. |
 | DE analysis | Wilcoxon test in Seurat, RegionalST | Identifying differentially expressed genes across spatial regions or cell types. |
 | Gene set enrichment analysis | GSEA, gProfiler, fgsea, clusterProfiler, EnrichR | Functional enrichment analysis for spatially resolved genes to identify biological pathways. |
 | Gene regulatory network | SCENIC, GRNBoost2, GENIE3 | Inferring regulatory networks to identify regulatory relationships. |
 | Deconvolution | Cell2location, RCTD, CARD, SpatialDWLS, BayesPrism | Deconvolution of SRT data using paired scRNA-seq data. |
 | CNV inference | SpatialInferCNV, SPATA | Inference of CNVs from SRT data |
 | Cell-cell interaction | COMMOT, NCEM, NicheDE, NicheNet | Inference of cellular interactions from SRT data |
 | Cell type annotation | SingleR, scType, Seurat | Annotating cell types based on reference datasets or marker gene expression. |
 | Neighborhood analysis | Squidpy, Giotto, SpaOTsc | Understanding spatial relationships and clustering between cell types and tissue regions. |
 | Dimension reduction | SpatialPCA, PRECAST, PCA, NMF | Spatially aware dimension reduction and embedding for downstream analysis |
 | Spatial domain detection | BayesSpace, Louvain (Seurat), SpaGCN, BASS | Identifying spatial domains and tissue structures using spatial relationships and gene expression. |
 | Spatially variable genes detection | SPARK, SPARK-X, nnSVG, CELINA | Detecting genes with significant spatial expression patterns, including cell type-specific patterns. |
 | Multi-omics integration | SpatialGLUE, MOFA+, StabMap | Integrating spatial multi-omics data for comprehensive biological insights. |
 | Trajectory analysis | Monocle3, Slingshot, STREAM | Analyzing developmental trajectories or pseudotime. |
 | Data visualization | SpatialView, Seurat, Scanpy, Squidpy, Circos | Visualization of spatial transcriptomics data in 2D/3D contexts. |
 | Imputation and Alignment | CytoSPACE, Tangram, CellTrek, PASTA | Mapping single-cell RNA-seq data onto spatial data for alignment and high-resolution insights. |
 | Power analysis and sample size | PoweREST | Calculating statistical power and determining sample size for spatial transcriptomics studies. |
 | Cell segmentation | Baysor, SCS, DeepCell, Cellpose, StarDist | Identifying and segmenting individual cells or nuclei from spatial images. |
 | Morphology integration | SpaGCN, iStar, METI | Integrating morphological information from H&E images with spatial transcriptomics. |
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