VoltRon will incorporate multiple data integration modules to achieve data transfer across a diverse set of modalities. We utilize the OpenCV library which fully embedded into VoltRon using Rcpp, hence VoltRon can align reference images of spatial datasets using computer vision and image registration. Users can automaticaly or manually align a list of images (H&E, microscopy or DAPI images) using a small shiny app incorporated within our analysis workflow.
In addition, VoltRon integrates with spot deconvolution methods such as RCTD to infer spot transcriptomics assays such as Visium and DBIT-Seq. We estimate the cell type abundances from a reference single cell data (Seurat, SingleCellExperiment etc.) with already annotated cell types. Then we generate additional assays associated with layers of the VoltRon object, and implement clustering on normalized cell type abundance data to discover niches in the dataset.
Spatial Data Alignment Automated and manual alignment of spatial data assays |
Multi-omic Integration Integrating data modalities within or across tissue sections |
Niche Clustering Clustering with ROI/spot deconvolution |
VoltRon is also capable of end-to-end analysis of diverse set of spatial data types such as ROIs (regions of interest), spots, single cells, molecules and even images. VoltRon incorporates built-in functions to import readouts of these distinct spatial omic technologies where a similar set of functions can be used to analyze each individual data type.
Region of Interests (ROIs) Quality control, analysis and visualization of ROI segments |
Cells/Spots Quality control, analysis and visualization of Cell/Spot datasets |
Molecules
Analysis and visualization of Molecule datasets |
Pixels (Image Only)
Analysis and visualization of Image datasets |
Here, we provide a group of tutorials to use additional features of the VoltRon objects. Here we describe a collection of features that VoltRon package utilizes such as interactive analysis and importing spatially aware data from diverse spatial omic technologies. VoltRon will be able to convert its objects to a diverse set of objects/datatypes commonly incorporated spatial data analysis (Seurat, SpatialExperiment, Giotto, anndata, SpatialData etc.)
Interactive Utilities
Interactive annotation and visualization |
Working with VoltRon Objects Manipulating and configuring VoltRon objects |
Importing Spatial Data
Importing readouts of spatial technologies |
Converting VoltRon Objects Converting VoltRon objects into Seurat,de Squidpy (anndata) etc. |