assess_cell_quality_PCA: ASSESS CELL QUALITY USING PCA AND OUTLIER DETECTION

In ti243/cellity: Quality Control for Single-Cell RNA-seq Data

Description

ASSESS CELL QUALITY USING PCA AND OUTLIER DETECTION

Usage

assess_cell_quality_PCA(features, file = "")

Arguments

features	Input dataset containing features (cell x features)
file	Output_file where plot is saved

Details

This function applies PCA on features and uses outlier detection to determine which cells are low and which are high quality

Value

Returns a dataframe indicating which cell is low or high quality (0 or 1 respectively)

Examples

data(training_mES_features)
training_mES_features_all <- training_mES_features[[1]]
training_quality_PCA_allF <- assess_cell_quality_PCA(training_mES_features_all)

ti243/cellity documentation built on May 31, 2019, 11:18 a.m.