This function computes summary statistics for signature-level bootstraps, including quantiles, min/max contribution proportions, and an experimental p-value.
Arguments
- bootstraps
A data frame containing bootstrap results in a sigverse-style format. See
sigshared::example_bootstraps()
for an example format.- threshold
The minimum proportion of mutations that must be explained by a signature for it to be considered present in a bootstrap. This threshold is used for calculating the experimental p-value via
sig_compute_experimental_p_value()
.- outliers_as_strings
Logical. Return outliers as a character vector of '|' delimited strings rather than as a list-column (ignored if
return_dataframe = FALSE
). Can customise the delimiter using thedelim
argument
Value
A data frame containing the following columns:
- signatures
Names of the signatures.
- quantiles, iqr, min, max,outlier_thresholds
Statistical summary columns (quantiles, min, and max) of the contribution proportions across bootstraps.
- outliers
either a list column or a character of '|' outlier strings (depending on
outliers_as_strings
argument- p_value
Computed experimental p-value for each signature, based on the threshold.
Examples
library(sigshared)
bootstraps <- example_bootstraps()
sig_summarise_bootstraps(bootstraps, threshold = 0.05)
#> signatures min max q1 q3 iqr median outlier_low_threshold
#> 1 Signature1 0.3 0.5 0.35 0.45 0.1 0.4 0.2
#> 2 Signature2 0.5 0.7 0.55 0.65 0.1 0.6 0.4
#> outlier_high_threshold outliers p_value
#> 1 0.6 0
#> 2 0.8 0