Select Genes Based on Statistical Thresholds from an anglemania_object

Selects genes from an anglemania_object-class based on specified thresholds for the absolute mean z-score and signal-to-noise ratio (SNR) z-score. It updates the integration_genes slot of the anglemania_object with the selected genes and associated information.

Usage

select_genes(
  angl,
  zscore_mean_threshold = 2,
  zscore_sn_threshold = 2,
  max_n_genes = NULL
)

Arguments

angl: An anglemania_object containing statistical matrices such as mean z-scores and SNR z-scores.
zscore_mean_threshold: Numeric value specifying the threshold for the absolute mean z-score. Default is 2.
zscore_sn_threshold: Numeric value specifying the threshold for the SNR z-score. Default is 2.
max_n_genes: Integer specifying the maximum number of genes to select. If NULL, all genes that pass the thresholds are used. Default is NULL.

Value

The input anglemania_object with the integration_genes slot updated to include the selected genes and their statistical information.

Details

The function performs the following steps:

Checks if the input object is of class anglemania_object-class.
If max_n_genes is not specified, it uses all genes that pass the thresholds.
Identifies gene pairs where both the mean z-score and SNR z-score exceed the specified thresholds.
If no gene pairs meet the criteria, it adjusts the thresholds to the 99th percentile values of the corresponding statistics and re-selects.
Extracts unique genes from the selected gene pairs using extract_rows_for_unique_genes.
Updates the integration_genes slot of the anglemania_object with the selected genes and their statistics.

Examples

se <- SeuratObject::pbmc_small
angl <- create_anglemania_object(se, batch_key = "groups")
#> No dataset_key specified.
#> Assuming that all samples belong to the same dataset and are separated by batch_key: groups
#> Extracting count matrices...
#> Filtering each batch to at least 1 cells per gene...
#> Using the intersection of filtered genes from all batches...
#> Number of genes in intersected set: 228
#> 
  |                                                  | 0 % elapsed=00s   
  |==================================================| 100% elapsed=00s, remaining~00s
angl <- anglemania(angl)
#> Computing angles and transforming to z-scores...
#> 
  |                                                  | 0 % elapsed=00s   
  |=========================                         | 50% elapsed=00s, remaining~00s
  |==================================================| 100% elapsed=00s, remaining~00s
#> Computing statistics...
#> Weighting matrix_list...
#> Calculating mean...
#> Calculating sds...
#> Filtering features...
angl <- select_genes(angl,
                      zscore_mean_threshold = 2.5,
                     zscore_sn_threshold = 2.5,
                     max_n_genes = 2000)
anglemania_genes <- get_anglemania_genes(angl)
# View the selected genes and use for integration