identify_outliers: Explore samples that are outliers

In Sage-Bionetworks/sageseqr: Identify differentially expressed genes counts data

Explore samples that are outliers

Description

Samples that are z standard deviations (SDs) from the mean of principal components (PC) 1 and 2 are identified as outliers.

Usage

identify_outliers(filtered_counts, clean_metadata, color, shape, size, z = 4)

Arguments

filtered_counts	A counts data frame with genes removed that have low expression.
clean_metadata	A data frame with sample identifiers as rownames and variables as factors or numeric as determined by "sageseqr::clean_covariates()".
color	Discrete variable in 'clean_metadata' differentiated by color.
shape	Discrete variable in 'clean_metadata' differentiated by shape.
size	Continuous variable in 'clean_metadata' differentiated by size.
z	Allowable number of standard deviations (SDs) from the mean. Defaults to 4.

Sage-Bionetworks/sageseqr documentation built on June 13, 2024, 2:11 p.m.