filterByOutliers: filterByOutliers

In IMB-Computational-Genomics-Lab/ascend: ascend - Analysis of Single Cell Expression, Normalisation, and Differential expression

Description

Automatically filter cells based on expression levels. These values are then used to filter out cells based on the following criteria:

• Low overall gene expression.

• Low number of expressed genes.

• Expression of control genes beyond set threshold.

Usage

filterByOutliers(object, cell.threshold = 3, gene.threshold = 3,
  control.threshold = 3)

Arguments

object	An EMSet.
cell.threshold	Mean Absolute Deviation (MAD) value to filter cells by library size. Default: 3.
gene.threshold	Mean Absolute Deviation (MAD) value to filter cells by number of expressed genes. Default: 3
control.threshold	Mean Absolute Deviation (MAD) value to filter cells by proportion of control genes. Default: 3.

Details

This function then loads the filtered expression matrix into the EMSet.

Value

An EMSet with outlier cells filtered out.

Examples

# Load EMSet
raw_emset <- ascend::raw_set

# Filter by outliers with default settings
filtered_emset <- filterByOutliers(raw_emset, cell.threshold = 3, 
gene.threshold = 1.5, control.threshold = 3)

IMB-Computational-Genomics-Lab/ascend documentation built on Aug. 29, 2019, 4:10 a.m.