dropMarkers: Filter out markers

View source: R/analyze.R

dropMarkersR Documentation

Filter out markers

Description

Filters out markers based on the percentage of missing values, low-expression and low-variability rates.

Usage

dropMarkers(dat, percent_NA = 0.2, low_mean_and_std = 0.05,
q_low_var = 0.25, force_drop = NULL)

Arguments

dat

an object of log2-normalized protein (or gene) expressions, containing markers in rows and samples in columns.

percent_NA

a constant in [0,1], the percentage of missing values that will be tolerated in the filtered data.

low_mean_and_std

a constant in [0,inf], the lower-bound of the mean or standard deviation of a marker in the filtered data.

q_low_var

a constant in [0,1], the quantile of marker variances which serves as a lower-bound of the marker variances in the filtered data.

force_drop

character array containing the marker names that user specifically wants to filter out.

Value

filtered data with the same format as the input data.

the row names (markers) of the data that are filtered out due to low-expression or low-variability.

Examples

dat = setNames(as.data.frame(matrix(1:(5*10),5,10),
row.names = paste('marker',1:5,sep='')), paste('sample',1:10,sep=''))
dat[1,1:2] = NA # marker1 have 20% missing values
dropMarkers(dat, percent_NA = .2) # marker1 is filtered out

Huang-lab/oppti documentation built on March 26, 2023, 12:52 p.m.