calculate_noise_threshold_method_statistics: Function to tabulate statistics for different methods of...

In noisyr: Noise Quantification in High Throughput Sequencing Output

Description

This function is used to tabulate and compare different combinations of similarity threshold and method to calculate the noise threshold for a given expression matrix.

Usage

calculate_noise_threshold_method_statistics(
  expression,
  similarity.threshold.sequence = 0.25,
  method.chosen.sequence = noisyr::get_methods_calculate_noise_threshold(),
  dump.stats = NULL,
  ...
)

Arguments

expression	either an expression summary (as calculated by calculate_expression_similarity_counts or calculate_expression_similarity_transcript), which should be a list with 3 slots: expression.matrix, expression.levels, expression.levels.similarity; alternatively, just an expression matrix; only density based methods are available for the latter case
similarity.threshold.sequence	similarity (correlation or inverse distance) threshold(s) to be used to find corresponding noise threshold; can be a single value or a numeric vector; the default, 0.25 is usually suitable for the Pearson correlation (the default similarity measure)
method.chosen.sequence	methods to use to calculate the noise thresholds, must be a subset of get_methods_calculate_noise_threshold; defaults to all
dump.stats	name of csv to export different thresholds calculated (optional)
...	other arguments (for the boxplot methods) passed to calculate_noise_threshold

Value

A tibble containing information on noise thresholds calculated using the input similarity thresholds and methods (optionally written in a csv file). The columns list the chosen method and similarity threshold, the minimum, mean, coefficient of variation, and maximum of the noise thresholds, and all the noise thresholds concatenated as a string.

See Also

calculate_noise_threshold

Examples

expression.summary <- calculate_expression_similarity_counts(
    expression.matrix = matrix(1:100, ncol=5),
    method = "correlation_pearson",
    n.elements.per.window = 3)
calculate_noise_threshold_method_statistics(expression.summary)

noisyr documentation built on April 16, 2021, 5:07 p.m.