Single-Cell Data Screening

Integrates matched bulk expression data and phenotype information to identify phenotype-associated cell populations in single-cell RNA-seq data using one of four computational methods. Ensures consistency between bulk and phenotype data before analysis.

Usage

Screen(
  matched_bulk,
  sc_data,
  phenotype,
  label_type = NULL,
  phenotype_class = c("binary", "survival", "continuous"),
  screen_method = c("Scissor", "scPP", "scPAS", "scAB"),
  ...
)

Arguments

matched_bulk

Matrix or data frame of preprocessed bulk RNA-seq expression data (genes x samples). Column names must match names/IDs in phenotype.

sc_data

A Seurat object containing scRNA-seq data to be screened.

phenotype

Phenotype data, either: - Named vector (names match matched_bulk columns), or - Data frame with row names matching matched_bulk columns

label_type

Character specifying phenotype label type (e.g., "SBS1", "time")

phenotype_class

Type of phenotypic outcome (must be consistent with input data): - "binary": Binary traits (e.g., case/control) - "continuous": Continuous measurements (only for Scissor, scPAS, scPP) - "survival": Survival objects

screen_method

Screening algorithm to use, there are four options: - "Scissor": see also DoScissor() - "scPP": see also DoscPP() - "scPAS": see also DoscPAS() - "scAB": see also DoscAB(), no continuous support

...

Additional method-specific parameters:

Scissor

alpha

(numeric or NULL) Significance threshold. When NULL, alpha will keep increasing iteratively until the corresponding cells are screened out, default 0.05

cutoff

(numeric) A threshold for terminating the iteration of alpha, only work when alpha is NULL, default 0.2

path2load_scissor_cache

(character) default NULL

path2save_scissor_inputs

(character) A path to save the intermediary data. By using path2load_scissor_cache, the intermediary data can be loaded from the specified path. default "Scissor_inputs.RData"

nfold

(integer) Cross-validation folds for reliability test, default 10

reliability_test

(logical) Whether to perform reliability test, default FALSE

scPP

ref_group

(integer or character) Reference group or baseline for binary comparisons, e.g. "Normal" for Tumor/Normal studies and 0 for 0/1 case-control studies. default: 0

Log2FC_cutoff

(numeric) Minimum log2 fold-change for binary markers, default 0.585

estimate_cutoff

(numeric) Effect size threshold for continuous traits, default 0.2

probs

(numeric) Quantile cutoff for cell classification, default 0.2

scPAS

assay

(character) Assay to use from sc_data, default "RNA"

imputation

(logical) Whether to perform imputation, default FALSE

nfeature

(integer) Number of features to select, default 3000

alpha

(numeric or NULL) Significance threshold, When NULL, alpha will keep increasing iteratively until the corresponding cells are screened out, default 0.01

independent

(logical) The background distribution of risk scores is constructed independently of each cell. default: TRUE

network_class

(character) Network class to use. default: 'SC', indicating gene-gene similarity networks derived from single-cell data. The other one is 'bulk'.

permutation_times

(integer) Number of permutations, default 2000

FDR_threshold

(numeric) FDR value threshold for identifying phenotype-associated cells default 0.05

scAB

alpha

(numeric) Coefficient of phenotype regularization ,default 0.005

alpha_2

(numeric) Coefficent of cell-cell similarity regularization, default 5e-05

maxiter

(integer) NMF optimization iterations, default 2000

tred

(integer) Z-score threshold, default 2

Value

A list containing:

scRNA_data

Filtered Seurat object with phenotype-associated cells

Some screen_result

Important information about the screened result related to the selected method

Data Matching Requirements

• matched_bulk column names and phenotype names/rownames must be identical

• Phenotype values must correspond to bulk samples (not directly to single cells)

• Mismatches will trigger an error before analysis begins, and there is a built-in pre-run check.

Method Compatibility

Method	Supported Phenotypes	Additional Parameters
Scissor	All three types	alpha, cutoff, path2load_scissor_cache, path2save_scissor_inputs, nfold, reliability_test, reliability_test_n
scPP	All three types	ref_group, Log2FC_cutoff, estimate_cutoff, probs
scPAS	All three types	n_components ,assay, imputation,nfeature, alpha,network_class,permutation_times,FDR_threshold,independent
scAB	Binary/Survival	alpha, alpha_2, maxiter, tred

See also

Associated functions:

• DoScissor

• DoscPP

• DoscPAS

• DoscAB