Computes module preservation statistics in a query dataset for a given reference dataset
Usage
ModulePreservation(
seurat_obj,
seurat_ref,
name,
n_permutations = 500,
parallel = FALSE,
seed = 12345,
gene_mapping = NULL,
genome_ref_col = NULL,
genome_query_col = NULL,
return_raw = FALSE,
wgcna_name = NULL,
wgcna_name_ref = NULL,
...
)Arguments
- seurat_obj
A Seurat object
- seurat_ref
A Seurat object serving as the reference for the module preservation analysis
- name
The name to give the module preservation analysis.
- n_permutations
Number of permutations for the module preservation test.
- parallel
logical determining whether to run preservation analysis in parallel
- seed
random seed for the permutation analysis.
- gene_mapping
a dataframe containing gene name mappings between the query and the reference dataset. One column should have the gene name in the query dataset, and anotehr column should have the corresponding gene name in the reference dataset.
- genome_ref_col
the column name containing the gene names for the reference dataset
- genome_query_col
the column name containing the gene names for the query dataset
- return_raw
if TRUE, returns the module preservation statistics, else returns seurat_obj with the stats added to the hdWGCNA experiment.
- wgcna_name
The name of the hdWGCNA experiment in the seurat_obj@misc slot
- wgcna_name_ref
The name of the hdWGCNA experiment in the seurat_ref@misc slot
Details
ModulePreservation performs a statistical test to assess the preservation of co-expression modules identified in one dataset in an independent dataset. This method is originally described by Langfelder et al. in the 2011 paper "Is My Network Module Preserved and Reproducible?". This method can be used to assess biological differences in networks, as well as technical differences / reproducibility across different batches.