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

Description Usage Arguments Value

View source: R/Cov_value.R

Description

rho_hat: Relative coverage change for each cell in a region

Usage

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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 Feb. 21, 2022, 9:57 a.m.