calculate_differential_prioritization: Perform a statistical test for differential prioritization

In neurorestore/Augur: Cell type prioritization in high-dimensional single-cell data

Perform a statistical test for differential prioritization

Description

Execute a permutation test to identify cell types with statistically significant differences in AUC between two different rounds of cell type prioritization (for instance, the response to drugs A and B, as compared to a common untreated control).

Usage

calculate_differential_prioritization(
  augur1,
  augur2,
  permuted1,
  permuted2,
  n_subsamples = 50,
  n_permutations = 1000
)

Arguments

augur1	Augur results from condition 1, obtained from calculate_auc
augur2	Augur results from condition 2, obtained from calculate_auc
permuted1	permuted Augur results from condition 1, obtained from calculate_auc with the argument augur_mode = "permute"
permuted2	permuted Augur results from condition 2, obtained from calculate_auc with the argument augur_mode = "permute"
n_subsamples	the number of subsamples to pool when calculating the mean AUC for each permtation; defaults to 50
n_permutations	the total number of mean AUCs to calculate from a background distribution

Value

a data frame containing the following columns:

1. cell_type: the cell types in the input dataste

2. auc.x: the AUC in condition 1

3. auc.y: the AUC in condition 2

4. delta_auc: the difference in AUCs between conditions

5. b number of times an equally large difference in AUCs was observed in the permuted data

6. m: total number of permutations performed

7. z: the z score of the observed delta-AUC, relative to the null distribution

8. pval: the permutation p-value for the observed delta-AUC

9. padj: the BH-corrected p-value

neurorestore/Augur documentation built on Feb. 28, 2024, 3:03 a.m.