diagnose {scBFA}R Documentation

Perform diagnoisis of dispersion on the expression profile to check whether scBFA works on specific dataset

Description

Perform diagnoisis of dispersion on the expression profile to check whether scBFA works on specific dataset

Usage

diagnose(
  scData,
  sampleInfo = NULL,
  disperType = "Fitted",
  diagnose_feature = "dispersion"
)

Arguments

scData

can be a raw count matrix, in which rows are genes and columns are cells; can be a seurat object; can be a SingleCellExperiment object.

sampleInfo

sample level feature matrix,e.g batch effect,experimental conditions in which rows are cells,columns are number of covariates.Default is NULL

disperType

a parameter to tell which dispersion estimate the user can plot DESeq2 offers stepwise dispersion estimate, a gene wise dispersion estimate using "GeneEst", dispersion estimate from fitted disperions ~ mean curve (using "Fitted") And final MAP estimate,using "Map". Default value is "Fitted"

diagnose_feature

a parameter to determine whether the user want to check GDR or dispersion.

Value

A Figure to tell the where the input data's dispersion ~ tpm curve align to the 14 benchmark datasets in Figure 2.a or Gene detection rate

Examples


data(exprdata)
diagnose(scData = exprdata)

[Package scBFA version 1.8.0 Index]