STgradient: Tests of gene expression spatial gradients

Calculates Spearman's coefficients to detect genes showing expression spatial gradients

STgradient(
  x = NULL,
  samples = NULL,
  topgenes = 2000,
  annot = NULL,
  ref = NULL,
  exclude = NULL,
  out_rm = F,
  limit = NULL,
  distsumm = "min",
  min_nb = 3,
  robust = T,
  cores = NULL
)

Arguments

x

an STlist with transformed gene expression

samples

the samples on which the test should be executed

topgenes

the number of high-variance genes to be tested. These genes are selected in descending order of variance as caclulated using Seurat's vst method

annot

the name of a column in @spatial_meta containing the tissue domain assigmemnts for each spot or cell. These assignents can be generated using the STclust function

ref

one of the tissue domains in the column specified in annot, corresponding to the "reference" cluster or domain. Spearman's correlations will be calculated using spots assigned to domains other than this reference domain (or domains specified in exclude).

exclude

optional, a cluster/domain to exclude from the analysis

out_rm

logical (optional), remove gene expression outliers defined by the interquartile method. This option is only valid when robust=F

limit

limite the analysis to spots/cells with distances to ref shorther than the value specified here. Useful when gradients might occur at smaller scales or when the domain in ref is scattered through the tissue. Caution must be used due to difficult interpretation of imposed limits. It is suggested to run analysis without restricted distances in addition for comparison.

distsumm

the distance summary metric to use in correlations. One of min or avg

min_nb

the minimum number of immediate neighbors a spot or cell has to have in order to be included in the analysis. This parameter seeks to reduce the effect of isolated ref spots on the correlation

robust

logical, wheter to use robus regression (MASS and sfsmisc packages)

cores

the number of cores used during parallelization. If NULL (default), the number of cores is defined automatically

Value

a list of data frames with the results of the test

Details

The STgradient function fits linear models and calculates Spearman coefficients between the expression of a gene and the minimum or average distance of spots or cells to a reference tissue domain. In other wordsm the STgradient function can be used to investigate if a gene is expressed higher in spots/cells closer to a specific reference tissue domain, compared to spots/cells farther from the reference domain (or viceversa as indicated by the Spearman's cofficient).