RA3_motif: Motif enrichment analysis based on the latent features output...

In cuhklinlab/RA3: The R-based implementation of "A reference-guided approach for epigenetic characterization of single cells".

Description

The output of RA3 can also be implemented in motif enrichment analysis. This function uses the extracted features from RA3 for motif analysis though package chromVAR .

Usage

RA3_motif(
  peaks,
  label_true,
  label_est,
  sc_mat,
  cluster_peak_num = 1000,
  motif_num = 50
)

Arguments

peaks	a vector containing peak information of the scCAS data, with elements formatted as 'chr1_24516561_24517061'
label_true	true cell labels
label_est	the estimated cluster labels, starting from 1
sc_mat	scCAS count matrix
cluster_peak_num	number of peaks selected for each cluster, default value is 1000
motif_num	number of motifs shown in the plot, default value is 50

Value

A list containing following items:

metaDataInd	cell index grouped by clustering results and cell labels
top_devs	derivation scores estimated using chromVAR

Examples

result <- RA3_motif(peaks, label_true, label_est, sc_mat,cluster_peak_num=1000, motif_num=50)

cuhklinlab/RA3 documentation built on March 18, 2021, 4:38 p.m.