process_raw_scseq: Process Count Data for App

View source: R/import_scseq.R

process_raw_scseqR Documentation

Process Count Data for App

Description

Performs the following: - normalization - adds HVGs - dimensionality reduction - clustering

Usage

process_raw_scseq(
  scseq,
  dataset_name,
  sc_dir,
  tx2gene_dir,
  cluster_alg = "leiden",
  npcs = 30,
  resoln = 1,
  hvgs = NULL,
  ref_name = NULL,
  founder = NULL,
  progress = NULL,
  value = 0
)

Arguments

scseq

SingleCellExperiment

dataset_name

Name of dataset to save

sc_dir

Directory to save dataset to

tx2gene_dir

Path to directory containing transcript to gene maps produced by load_tx2gene.

cluster_alg

Cluster algorith. Either 'leiden' (default) or 'walktrap'.

npcs

Number of principal components to use. Default is 30.

resoln

resolution_parameter used by cluster_leiden if cluster_alg = 'leiden'.

hvgs

Character vector of a priori genes to use for PCA. If NULL (default), highly variable genes are calulated by getTopHVGs.

ref_name

Name of symphony or Azimuth reference to use for reference-based analysis.

founder

Name of original founding dataset (may be ancestor of from_dataset).

progress

Shiny progress object. Default (NULL) prints to stdout.

value

Initial value of progress.

Details

Then calls run_post_cluster


hms-dbmi/drugseqr documentation built on Feb. 15, 2024, 10:38 p.m.