Data Science
Data Analysis Tools and Resources
The following resources and tools are provided by Dr. Liang Li and Dr. Lulu Shang. If you have question or need assistance, please contact us at TBEL-CDMC@mdanderson.org
Task
Approach
Tools
Applications
Quality Control
Quality Control of Spatial Transcriptomics Data, Removing Ambient RNA Contamination.
Batch Effect Removal
Harmony, ComBat, BBKNN
Correcting Batch effects across datasets.
Wilcoxon Test in Seurat, RegionalST
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 Analysis
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.
