auto_cna_signal: Automated pipeline to compute CNA signal from scRNA...

In jmonlong/scCNAutils: Functions to analyze copy number aberrations in single-cell data

Automated pipeline to compute CNA signal from scRNA expression

Description

Goes from reading raw gene counts to CNA-level signal, tSNE and community detection.

Usage

auto_cna_signal(
  data,
  genes_coord,
  prefix = "scCNAutils_out",
  nb_cores = 1,
  pause_after_qc = FALSE,
  use_cache = TRUE,
  sample_names = NULL,
  info_df = NULL,
  max_mito_prop = 0.2,
  min_total_exp = 0,
  cells_sel = NULL,
  chrs = c(1:22, "X", "Y"),
  cell_cycle = NULL,
  bin_mean_exp = 3,
  rm_cv_quant = NULL,
  z_wins_th = 3,
  smooth_wsize = 3,
  cc_sd_th = 3,
  nb_pcs = 10,
  comm_k = 100,
  viz = c("tsne", "umap", "both"),
  tsne.seed = 999,
  rcpp = TRUE
)

Arguments

data	a data.frame with gene expression or the path to the folder with the 'matrix.mtx', 'genes.tsv' and 'barcodes.tsv' files. A list if multiple samples.
genes_coord	either a file name or a data.frame with coordinates and gene names.
prefix	the prefix to use for the files created by this function (e.g. graphs).
nb_cores	the number of processors to use.
pause_after_qc	pause after the QC to pick custom QC thresholds.
use_cache	should intermediate files used and avoid redoing steps?
sample_names	the names of each sample. If NULL, tries to use data's names.
info_df	a data.frame with information about cells.
max_mito_prop	the maximum proportion of mitochondrial RNA.
min_total_exp	the minimum total cell expression
cells_sel	consider only these cells. Other cells filtered no matter what.
chrs	the chromosome names to keep. NULL to include all the chromosomes.
cell_cycle	if non-null, either a file or data.frame to compute cell cycle scores. See details.
bin_mean_exp	the desired minimum mean expression in the bin.
rm_cv_quant	the quantile threshold to remove CV outlier. Default NULL (i.e. not used).
z_wins_th	the threshold to winsorize Z-score. Default is 3
smooth_wsize	the window size for smoothing. Default is 3.
cc_sd_th	the number of SD used for the thresholds when defining cycling cells.
nb_pcs	the number of PCs used in the community detection or tSNE.
comm_k	the number of nearest neighbor for the KNN graph. Default 100.
viz	which method to use for visualization ('tsne', 'umap' or 'both'). Default is 'tsne'.
tsne.seed	the seed for the tSNE.
rcpp	use Rcpp function. Default is TRUE. More memory-efficient and faster when running on one core.

Value

a data.frame with QC, community and tSNE for each cell.

Author(s)

Jean Monlong

jmonlong/scCNAutils documentation built on Feb. 8, 2025, 8:09 a.m.