SpatialDecon-package: SpatialDecon: A package for estimating mixed cell type...

In Nanostring-Biostats/SpatialDecon: Deconvolution of mixed cells from spatial and/or bulk gene expression data

SpatialDecon: A package for estimating mixed cell type abundance in the regions of spatially-resolved gene expression studies

Description

The SpatialDecon package estimates mixed cell type abundance in the regions of spatially-resolved gene expression studies, using the method of Danaher & Kim (2020), "Advances in mixed cell deconvolution enable quantification of cell types in spatially-resolved gene expression data." It is also appropriate to apply to bulk gene expression data.

functions

Functions to help set up deconvolution:

• derive_GeoMx_background Estimates the background levels from GeoMx experiments

• collapseCellTypes reformats deconvolution results to merge closely-related cell types

• download_profile_matrix Downloads a cell profile matrix.

• safeTME: a data object, a matrix of immune cell profiles for use in tumor-immune deconvolution.

Deconvolution functions:

• spatialdecon runs the core deconvolution function

• reverseDecon runs a transposed/reverse deconvolution problem, fitting the data as a function of cell abundance estimates. Used to measure genes' dependency on cell mixing and to calculate gene residuals from cell mixing.

Plotting functions:

• florets Plot cell abundance on a specified x-y space, with each point a cockscomb plot showing the cell abundances of that region/sample.

• TIL_barplot Plot abundances of tumor infiltrating lymphocytes (TILs) estimated from the safeTME cell profile matrix

Examples

data(mini_geomx_dataset)
data(safeTME)
data(safeTME.matches)
# estimate background:
mini_geomx_dataset$bg <- derive_GeoMx_background(
  norm = mini_geomx_dataset$normalized,
  probepool = rep(1, nrow(mini_geomx_dataset$normalized)),
  negnames = "NegProbe"
)
# run basic decon:
res0 <- spatialdecon(
  norm = mini_geomx_dataset$normalized,
  bg = mini_geomx_dataset$bg,
  X = safeTME
)
# run decon with bells and whistles:
res <- spatialdecon(
  norm = mini_geomx_dataset$normalized,
  bg = mini_geomx_dataset$bg,
  X = safeTME,
  cellmerges = safeTME.matches,
  cell_counts = mini_geomx_dataset$annot$nuclei,
  is_pure_tumor = mini_geomx_dataset$annot$AOI.name == "Tumor"
)

Nanostring-Biostats/SpatialDecon documentation built on Jan. 26, 2024, 8:20 p.m.