A framework for SPAtial Transcriptomic Analysis: SPATA2v2
Visualization
Visualize gene expression, pathway enrichment and customized features within a spatial context.
DE-Analysis
Find and analyze differentially expressed genes across multiple regions and samples and visualize your results.
Spatial Trajectories
Draw spatial trajectories and display gradients of gene epression and pathway activity.
Spatial Trajectory Screening
Model gene expression along spatial trajectories and screen for biologically relevant gradients.
Image Annotations
Annotate histological microstructures and areas for image guided analysis.
Image Annotation Screening
Screen the immediate surrounding of histological structures to identify histology associated expression gradients.
Autoencoder Denoising
Use state of the art neural networks to denoise your data and obtain more insightful visualization and downstream analysis results.
Spatial Segmentation
Dissect the tissue in compartments and test for differentially expressed genes based on histology.
Copy-Number-Variations
Identify large-scale chromosomal gains and losses in data derived from malignancies.
