sig_genes_extract_all: Extract significant genes for all modeling results

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

Extract significant genes for all modeling results

Description

This function combines the output of sig_genes_extract() from all the layer-level (group-level) modeling results and builds the data required for functions such as layer_boxplot().

Usage

sig_genes_extract_all(
  n = 10,
  modeling_results = fetch_data(type = "modeling_results"),
  sce_layer = fetch_data(type = "sce_layer")
)

Arguments

n	The number of the top ranked genes to extract.
modeling_results	Defaults to the output of fetch_data(type = 'modeling_results'). This is a list of tables with the columns ⁠f_stat_*⁠ or ⁠t_stat_*⁠ as well as ⁠p_value_*⁠ and ⁠fdr_*⁠ plus ensembl. The column name is used to extract the statistic results, the p-values, and the FDR adjusted p-values. Then the ensembl column is used for matching in some cases. See fetch_data() for more details. Typically this is the set of reference statistics used in layer_stat_cor().
sce_layer	Defaults to the output of fetch_data(type = 'sce_layer'). This is a SingleCellExperiment object with the spot-level Visium data compressed via pseudo-bulking to the layer-level (group-level) resolution. See fetch_data() for more details.

Value

A DataFrame-class with the extracted statistics in long format. The specific columns are described further in the vignette.

See Also

Other Layer modeling functions: layer_boxplot(), sig_genes_extract()

Examples

## Obtain the necessary data
if (!exists("modeling_results")) {
    modeling_results <- fetch_data(type = "modeling_results")
}
if (!exists("sce_layer")) sce_layer <- fetch_data(type = "sce_layer")

## top 10 genes for all models
sig_genes_extract_all(
    modeling_results = modeling_results,
    sce_layer = sce_layer
)

LieberInstitute/spatialLIBD documentation built on Dec. 19, 2024, 7:12 p.m.