Select_normal: Identify candidate normal cells and normal regions for cell...

Description Usage Arguments Value

View source: R/Select_normal.R

Description

Identify candidate normal cells and normal regions for cell coverage normalization

Usage

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Select_normal(
  Obj_filtered = NULL,
  raw_counts = NULL,
  cell_nclust = 5,
  plot_theta = FALSE,
  pre_sel = FALSE,
  cell_type = NULL,
  cutree_rows = 3,
  mincell = NULL
)

Arguments

Obj_filtered

An Alleloscope object with major haplotype proportion (theta_hat) for each cell of each region in the "rds_list".

raw_counts

A large binned coverage matrix (bin by cell) with values being read counts for all chromosomal regions of tumor sample.

cell_nclust

Integer. Number of clusters used in identifying normal cells in the sample.

plot_theta

Logical (TRUE/FALSE). Whether or not to plot the hierarchical clustering result using the theta_hat values across regions.

pre_sel

Logical (TRUE/FALSE). Whether or not to use theta_hat from regions without segmentation (each chromosome) to identify normal cells for segmentation.

cell_type

A matrix with two columns: COL1- cell barcodes; COL2- cell types ("tumor" and others)

cutree_rows

Integer. Number of clusters the rows are divided into for visualization (inherited from the pheatmap function).

mincell

An integer to filter out regions with minimum number of cells.

Value

A Alleloscope object with a "select_normal" list added. A "select_normal" list includes "barcode_normal": Barcodes of the identified normal cells in the tumor sample. "region_normal": A vector of ordered potential normal regions for selection. (1st is the most possible.) "region_normal_rank": A table with the potential "normal regions" for the k clusters from hierarchical clustering. "k_normal": An integer indicates the kth clsuter that is idenfied as "normal cells"


seasoncloud/Alleloscope documentation built on June 18, 2021, 7:24 p.m.