Spatial Cellular Estimator for Tumors • SpaCET

SpaCET is an R package designed for analyzing cancer spatial transcriptomics (ST) datasets to estimate cell lineages and intercellular interactions within the tumor microenvironment. In a nutshell, SpaCET first infers cancer cell abundance by integrating a gene pattern dictionary of common malignancies. Subsequently, SpaCET employs a constrained linear regression model to calibrate local tissue densities and determine stromal and immune cell lineage fractions based on a comprehensive non-malignant cell atlas. Furthermore, SpaCET has the capability to unveil putative cell-cell interactions within the tumor microenvironment, particularly at the tumor-immune interface. Of note, although SpaCET does not require any input cell references for the analysis of tumor ST data, SpaCET can still incorporate a matched scRNA-seq dataset as customized references to conduct cell type deconvolution of any ST dataset.

Installation

To install SpaCET, we recommend using devtools:

# install.packages("devtools")
devtools::install_github("data2intelligence/SpaCET")

Or user can install SpaCET from the source code. Click here to download it.

# install SpaCET in the R environment.
install.packages("Path_to_the_source_code", repos = NULL, type="source")

Dependencies

R version >= 4.2.0.
R packages: Matrix, jsonlite, ggplot2, reshape2, scatterpie, patchwork, png, shiny, plotly, DT, MUDAN, factoextra, NbClust, cluster, parallel, pbmcapply, psych, BiRewire, limma, arrow, UCell.

Example

library(SpaCET)

visiumPath <- file.path(system.file(package = "SpaCET"), "extdata/Visium_BC")
SpaCET_obj <- create.SpaCET.object.10X(visiumPath = visiumPath)
SpaCET_obj <- SpaCET.deconvolution(SpaCET_obj, cancerType="BRCA", coreNo=6)

SpaCET_obj@results$deconvolution$propMat[1:13,1:5]

##                   50x102 59x19        14x94        47x13        73x43
## Malignant   2.860636e-01     1 6.845966e-02 3.899756e-01 9.608802e-01
## CAF         3.118545e-01     0 3.397067e-01 1.111980e-01 3.372692e-02
## Endothelial 5.510895e-02     0 1.427060e-01 3.080531e-02 5.263544e-03
## Plasma      2.213392e-02     0 1.507382e-02 1.183170e-02 9.071809e-06
## B cell      3.885793e-03     0 9.271616e-02 1.406470e-01 1.329085e-06
## T CD4       1.344389e-01     0 1.554305e-02 1.249414e-01 1.112392e-05
## T CD8       7.578696e-03     0 2.514558e-07 1.379856e-03 1.123043e-06
## NK          7.104005e-04     0 1.670019e-06 4.890387e-08 3.562557e-07
## cDC         1.421632e-07     0 8.278023e-02 7.584295e-02 2.851146e-07
## pDC         1.606443e-06     0 2.283754e-02 1.805671e-02 3.878344e-07
## Macrophage  1.703304e-01     0 5.021248e-02 9.531511e-02 9.253645e-07
## Mast        7.905067e-08     0 1.621498e-05 1.333430e-07 1.162099e-07
## Neutrophil  1.380073e-05     0 9.528996e-07 1.167503e-08 9.908635e-05

Tutorial

Data availability

This Link provides access to the 10 scRNA-seq datasets used to generate SpaCET’s in-house cell-type reference, along with the 8 spatial transcriptomics samples demonstrated in our manuscript.

Citation