registration_stats_pairwise: Spatial registration: compute pairwise statistics

In LieberInstitute/spatialLIBD: spatialLIBD: an R/Bioconductor package to visualize spatially-resolved transcriptomics data

Spatial registration: compute pairwise statistics

Description

This function computes the gene pairwise t-statistics (one group > another, for all combinations). These t-statistics can be used for spatial registration with layer_stat_cor() and related functions. Although, they are more typically used for identifying pairwise-marker genes.

Usage

registration_stats_pairwise(
  sce_pseudo,
  registration_model,
  block_cor,
  var_registration = "registration_variable",
  var_sample_id = "registration_sample_id",
  gene_ensembl = NULL,
  gene_name = NULL
)

Arguments

sce_pseudo	The output of registration_pseudobulk().
registration_model	The output from registration_model().
block_cor	A numeric(1) computed with registration_block_cor().
var_registration	A character(1) specifying the colData(sce_pseudo) variable of interest against which will be used for computing the relevant statistics.
var_sample_id	A character(1) specifying the colData(sce_pseudo) variable with the sample ID.
gene_ensembl	A character(1) specifying the rowData(sce_pseudo) column with the ENSEMBL gene IDs. This will be used by layer_stat_cor().
gene_name	A character(1) specifying the rowData(sce_pseudo) column with the gene names (symbols).

Value

A data.frame() with the pairwise statistical results. This is similar to fetch_data("modeling_results")$pairwise.

See Also

Other spatial registration and statistical modeling functions: registration_block_cor(), registration_model(), registration_pseudobulk(), registration_stats_anova(), registration_stats_enrichment(), registration_wrapper()

Examples

example("registration_block_cor", package = "spatialLIBD")
results_pairwise <- registration_stats_pairwise(sce_pseudo,
    registration_mod, block_cor,
    gene_ensembl = "ensembl", gene_name = "gene_name"
)
head(results_pairwise)

## Specifying `block_cor = NaN` then ignores the correlation structure
results_pairwise_nan <- registration_stats_pairwise(sce_pseudo,
    registration_mod,
    block_cor = NaN,
    gene_ensembl = "ensembl", gene_name = "gene_name"
)
head(results_pairwise_nan)

LieberInstitute/spatialLIBD documentation built on April 21, 2024, 6:47 p.m.