determine_outliers: determine outliers

In MoseleyBioinformaticsLab/visualizationQualityControl: Development of visualization methods for quality control

determine outliers

Description

determine outliers

Usage

determine_outliers(
  median_correlations = NULL,
  outlier_fraction = NULL,
  cor_weight = 1,
  frac_weight = 1,
  only_high = TRUE
)

Arguments

median_correlations	median correlations
outlier_fraction	outlier fractions
cor_weight	how much weight for the correlation score?
frac_weight	how much weight for the outlier fraction?
only_high	should only things at the low end of score be removed?

Details

For outlier sample detection, one should first generate median correlations using 'median_correlations', and outlier fractions using 'outlier_fraction'. If you only have one or the other, than you should use named arguments to only pass the one or the other.

Alternatively, you can change the weighting used for median correlations or outlier fraction, including setting them to 0.

Value

data.frame

MoseleyBioinformaticsLab/visualizationQualityControl documentation built on Feb. 21, 2024, 1:06 a.m.