View source: R/Select_normal.R
Select_normal | R Documentation |
Identify candidate normal cells and normal regions for cell coverage normalization
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 )
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. |
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"
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