transform_data: transform_data: Transformation of spatial transcriptomics...

In FridleyLab/spatialGE: Visualization and Analysis of Spatial Heterogeneity in Spatially-Resolved Gene Expression

transform_data: Transformation of spatial transcriptomics data

Description

Applies data transformation methods to spatial transcriptomics samples within an STlist

Usage

transform_data(
  x = NULL,
  method = "log",
  scale_f = 10000,
  sct_n_regr_genes = 3000,
  sct_min_cells = 5,
  cores = NULL
)

Arguments

x	an STlist with raw count matrices.
method	one of log or sct. If log, log-normalization is performed. If sct, then the SCTransform method is applied by calling sctransform::vst
scale_f	the scale factor used in logarithmic transformation
sct_n_regr_genes	the number of genes to be used in the regression model during SCTransform. The function sctransform::vst makes a random gene selection based on this number
sct_min_cells	The minimum number of spots/cells to be used in the regression model fit by sctransform::vst
cores	integer indicating the number of cores to use during parallelization. If NULL, the function uses half of the available cores at a maximum. The parallelization uses parallel::mclapply and works only in Unix systems.

Details

This function takes an STlist with raw counts and performs data transformation. The user has the option to select between log transformation after library size normalization (method='log'), or SCTransform (method='sct'). In the case of logarithmic transformation, a scaling factor (10^4 by default) is applied. The function uses parallelization using "forking" (not available in Windows OS). Note that the method sct returns a matrix with less genes as filtering is done for low expression genes.

Value

x an updated STlist with transformed counts.

Examples

# Using included melanoma example (Thrane et al.)
# Download example data set from spatialGE_Data
thrane_tmp = tempdir()
unlink(thrane_tmp, recursive=TRUE)
dir.create(thrane_tmp)
lk='https://github.com/FridleyLab/spatialGE_Data/raw/refs/heads/main/melanoma_thrane.zip?download='
download.file(lk, destfile=paste0(thrane_tmp, '/', 'melanoma_thrane.zip'), mode='wb')
zip_tmp = list.files(thrane_tmp, pattern='melanoma_thrane.zip$', full.names=TRUE)
unzip(zipfile=zip_tmp, exdir=thrane_tmp)
# Generate the file paths to be passed to the STlist function
count_files <- list.files(paste0(thrane_tmp, '/melanoma_thrane'),
                          full.names=TRUE, pattern='counts')
coord_files <- list.files(paste0(thrane_tmp, '/melanoma_thrane'),
                          full.names=TRUE, pattern='mapping')
clin_file <- list.files(paste0(thrane_tmp, '/melanoma_thrane'),
                        full.names=TRUE, pattern='clinical')
# Create STlist
library('spatialGE')
melanoma <- STlist(rnacounts=count_files[c(1,2)],
                   spotcoords=coord_files[c(1,2)],
                   samples=clin_file) # Only first two samples
melanoma <- transform_data(melanoma, method='log')

FridleyLab/spatialGE documentation built on April 14, 2025, 9:37 a.m.