diagnose: Perform diagnoisis of dispersion on the expression profile to...

Description Usage Arguments Value Examples

View source: R/diagnose.R

Description

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

Usage

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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

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quon-titative-biology/bfa documentation built on March 18, 2020, 11:53 a.m.