segment_CBScs: Cross-sample segmentation

In rujinwang/SCOPE: A normalization and copy number estimation method for single-cell DNA sequencing

Cross-sample segmentation

Description

SCOPE offers a cross-sample Poisson likelihood-based recursive segmentation, enabling shared breakpoints across cells from the same genetic background.

Usage

segment_CBScs(Y, Yhat, sampname, ref, chr, 
                    mode = "integer", max.ns)

Arguments

Y	raw read depth matrix after quality control procedure
Yhat	normalized read depth matrix
sampname	vector of sample names
ref	GRanges object after quality control procedure
chr	chromosome name. Make sure it is consistent with the reference genome.
mode	format of returned copy numbers. Only integer mode is supported for scDNA-seq data.
max.ns	a number specifying how many rounds of nested structure searching would be performed. Defalut is 0.

Value

A list with components

poolcall	Cross-sample CNV callings indicating shared breakpoints
finalcall	Final cross-sample segmented callset of CNVs with genotyping results
image.orig	A matrix giving logarithm of normalized z-scores
image.seg	A matrix of logarithm of estimated copy number over 2
iCN	A matrix of inferred integer copy number profiles

Author(s)

Rujin Wang [e-mail]

Examples

Yhat.sim <- normObj.scopeDemo$Yhat[[which.max(normObj.scopeDemo$BIC)]]
segment_cs_chr1 <- segment_CBScs(Y = Y_sim, Yhat = Yhat.sim,
                        sampname = colnames(Y_sim),
                        ref = ref_sim, chr = 'chr1', max.ns = 1)

rujinwang/SCOPE documentation built on Jan. 1, 2023, 5:40 a.m.