Cluster-Marker: Find Cluster Markers

In bioinfoDZ/RISC: Robust Integration of Single-Cell RNA-Seq Datasets

Find Cluster Markers

Description

This is the basic function in RISC, it can identify the cluster markers by comparing samples in the selected cluster to the samples of the rest clusters. Therefore, it is possible one gene labeled as a marker in more than one clusters. Two methods are employed in RISC, one is based on Negative Binomial model while the other using QuasiPoisson model.

Usage

scMarker(
  object,
  cluster = 1,
  positive = TRUE,
  frac = 0.25,
  log2FC = 0.5,
  Padj = 0.05,
  latent.factor = NULL,
  method = "QP",
  min.cells = 10,
  ncore = 1
)

Arguments

object	RISC object: a framework dataset.
cluster	Select the cluster that we want to detect cluster marker genes.
positive	Whether only output the cluster markers with positive log2FC.
frac	A fraction cutoff, the marker genes expressed at least a cutoff fraction of all the cells.
log2FC	The cutoff of log2 Fold-change for differentially expressed marker genes.
Padj	The cutoff of the adjusted P-value.
latent.factor	The latent factor from coldata, which represents number values or factors, and only one latent factor can be inputed.
method	Which method is used to identify cluster markers, three options: 'NB' for Negative Binomial model, 'QP' for QuasiPoisson model, and 'Wilcox' for Wilcoxon Rank Sum and Signed Rank model.
min.cells	The minimum cells for each cluster to calculate marker genes.
ncore	The multiple cores for parallel calculating.

Details

Because log2 cannot handle counts with value 0, we use log1p to calculate average values of counts and log2 to format fold-change.

References

Paternoster et al., Criminology (1997)

Berk et al., Journal of Quantitative Criminology (2008)

Liu et al., Nature Biotech. (2021)

Examples

# RISC object
obj0 = raw.mat[[3]]
obj0 = scPCA(obj0, npc = 10)
obj0 = scUMAP(obj0, npc = 3)
obj0 = scCluster(obj0, slot = "cell.umap", k = 3, method = 'density')
DimPlot(obj0, slot = "cell.umap", colFactor = 'Cluster', size = 2)
marker1 = scMarker(obj0, cluster = 1, method = 'QP', min.cells = 3)

bioinfoDZ/RISC documentation built on March 30, 2024, 9:19 p.m.