Cov_value: Normalize coverage using identified/ specified normal cells...

In seasoncloud/Alleloscope: Allele-specific copy number genotyping for single cell sequencing data

Normalize coverage using identified/ specified normal cells and one normal region and generate a table with (rho_hat) of each cell for all regions.

Description

rho_hat: Relative coverage change for each cell in a region

Usage

Cov_value(
  Obj_filtered = NULL,
  type = "tumor",
  raw_counts = NULL,
  ref_counts = NULL,
  cov_adj = 1,
  qt_filter = FALSE,
  refr = TRUE,
  plot_path = NULL
)

Arguments

Obj_filtered	An Alleloscope object with segments, specified normal cells and a normal region
type	Specify whether the sample is a "tumor" or "cellline". If "type" is a "cellline", param "ref_counts" needs to be specified for normal sample.
raw_counts	(required) A large binned coverage matrix (m1 bin by n1 cell) with values being read counts for all chromosomal regions of tumor sample.
ref_counts	(required only when type = "cellline") A binned coverage matrix (m2 bin by n2 cell) with values being read counts for all chromosomal regions of normal sample. n2 can be 1 for bulk sample.
cov_adj	An integer for coverage adjustment for tumor cells.
qt_filter	Logical (TRUE/ FALSE). Whether or not to exclude cells with rho_hat>0.99 or <0.01 for each region.
refr	Logical (TRUE/ FALSE). Whether or not to use diplid region for normalization (otherwise, cell size is used).

Value

(rho_hat) of each cell for all region in the "cov_values". Every column in the cov_values is (rho_hat) of each region. Each row is a cell.

seasoncloud/Alleloscope documentation built on March 17, 2023, 1:14 a.m.