Compute reference matrix from an `screference` object using BayesPrism

Usage

bayesprism_scref(
  scref,
  cache_path = "bayes_prism",
  data_type = c("10X", "Smart-seq")[1],
  malignant_pop_id = NULL,
  pval_cutoff = 0.01,
  logFC_cutoff = 0.1,
  ncores = parallel::detectCores()/2
)

Arguments

scref: an object of class `screference`
cache_path: path to cache the results
data_type: a string, one of: `"10X"` or `"Smart-seq"`
malignant_pop_id: the ID in the screference `annot_id` corresponding to the malignant cell population for deconvolution of cancer samples. If none of the populations are malignant, leave as `NULL`.
pval_cutoff: a float, p-value cutoff from differential expression analysis for selection of markers
logFC_cutoff: a float, cutoff for log fold-change from differential expression analysis between populations for selection of markers
n_cores: number of cores used for computation

Value

an screference object updated with BayesPrism reference

Note

Reference: Chu, T., Wang, Z., Pe’er, D. et al. Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology. Nat Cancer 3, 505–517 (2022). https://doi-org.insb.bib.cnrs.fr/10.1038/s43018-022-00356-3 See also: https://github.com/Danko-Lab/BayesPrism