findDAR: Identifiy Differential Accessible Regions (DARs)

View source: R/findDARs.R

findDARR Documentation

Identifiy Differential Accessible Regions (DARs)

Description

This function takes a snap object and finds differentially accessible regions (DARs) that define clusters.

Usage

findDAR(obj, input.mat, cluster.pos, cluster.neg, cluster.neg.method, bcv, fdr,
  pvalue, test.method, seed.use)

Arguments

obj

A snap object.

input.mat

Matrix to use for finding differential features c("bmat", "pmat", "gmat").

cluster.pos

Cluster to identify DAR markers.

cluster.neg

Cluster used as negative control compare with cluster.pos [NULL]. If cluster.neg is NULL, runFindDARs will automatically identifies background cells by finding those that are closest to cluster.pos cells as a local background.

cluster.neg.method

Method to find negative control cells if cluster.neg==NULL. ["knn", "random"]

bcv

Biological coefficient of variation. Typical values for the common BCV (square-rootdispersion) for datasets arising from well-controlled experiments are 0.4 for human data, 0.1 for data on genetically identical model organisms or 0.01 for technical replicates.

test.method

Test method for differential analysis c("exactTest", "LRT", "QLF").

seed.use

Random seeds.

Examples

data(demo.sp);
idy = findDAR(
obj=demo.sp, 
 input.mat="pmat", 
 cluster.pos=1, 
 bcv=0.1, 
 test.method="exactTest", 
 seed.use=10
 );


r3fang/SnapATAC documentation built on March 29, 2022, 4:33 p.m.