RankMSE: Calculate Mean Squared Error for nCount/nFeature Rank.

In zh542370159/dropSplit: Automatically identify cell-containing and empty droplets for droplet-based scRNAseq data using dropSplit

Calculate Mean Squared Error for nCount/nFeature Rank.

Description

Calculate Mean Squared Error for nCount/nFeature Rank.

Usage

RankMSE(
  meta_info,
  fill_RankMSE = FALSE,
  smooth_num = 3,
  smooth_window = 100,
  find_rank = FALSE,
  Empty_min_nCount = 10
)

Arguments

meta_info	A data.frame or DataFrame. Must contain the 'nCount' and 'nFeature' columns.
fill_RankMSE	Whether to fill the RankMSE by nCount. Default is TRUE.
smooth_num	Number of times to smooth(take a mean value within a window length smooth_window) the squared error. Default is 3.
smooth_window	Window length used to smooth the squared error. Default is 100.
find_rank	Whether to find the 'Cell' RankMSE valley, the 'Uncertain' RankMSE peak and the 'Empty' RankMSE valley. Default is FALSE.
Empty_min_nCount	Minimum nCount for 'Empty' droplets. Default is 10.

Value

A list include meta_info and cell_rank_count

zh542370159/dropSplit documentation built on June 19, 2022, 2:49 p.m.