norm_cell: Normalizing single cell data

In jianhaizhang/spatialHeatmap: spatialHeatmap: Visualizing Spatial Assays in Anatomical Images and Large-Scale Data Extensions

Normalizing single cell data

Description

A meta function for normalizing single-cell RNA-seq data.

Usage

norm_cell(
  sce,
  bulk = NULL,
  cpm = FALSE,
  count.kp = FALSE,
  quick.clus = list(min.size = 100, d = NULL),
  com.sum.fct = list(max.cluster.size = 3000, min.mean = 1),
  log.norm = list(),
  com = FALSE,
  wk.dir = NULL
)

Arguments

sce	Single cell count data in form of SingleCellExperiment after quality control, which is returned by qc_cell.
bulk	Bulk tissue count data in form of SingleCellExperiment, SummarizedExperiment, or data.frame.
cpm	Logical. If FALSE (default), the count data are only normalized by computeSumFactors. If TRUE, the data are first normalized by computeSumFactors then transformed to counts per million by calculateCPM.
count.kp	Logical. If FALSE (default), the count data is discarded and only log2-scale data are kept.
quick.clus	Arguments in a named list passed to quickCluster, such as quick.clus=list(min.size = 100).
com.sum.fct	Arguments in a named list passed to computeSumFactors, such as com.sum.fct=list(max.cluster.size = 3000)).
log.norm	Arguments in a named list passed to logNormCounts.
com	Logical, if TRUE the returned cell and bulk data are column-wise combined, otherwise they are separated in a list.
wk.dir	The directory path to save normalized data.

Value

A SingleCellExperiment object.

Author(s)

Jianhai Zhang [e-mail]
Dr. Thomas Girke [e-mail]

References

Amezquita R, Lun A, Becht E, Carey V, Carpp L, Geistlinger L, Marini F, Rue-Albrecht K, Risso D, Soneson C, Waldron L, Pages H, Smith M, Huber W, Morgan M, Gottardo R, Hicks S (2020). “Orchestrating single-cell analysis with Bioconductor.” Nature Methods, 17, 137–145. https://www.nature.com/articles/s41592-019-0654-x. Lun ATL, McCarthy DJ, Marioni JC (2016). “A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor.” F1000Res., 5, 2122. doi: 10.12688/f1000research.9501.2. McCarthy DJ, Campbell KR, Lun ATL, Willis QF (2017). “Scater: pre-processing, quality control, normalisation and visualisation of single-cell RNA-seq data in R.” Bioinformatics, 33, 1179-1186. doi: 10.1093/bioinformatics/btw777. Morgan M, Obenchain V, Hester J, Pagès H (2022). SummarizedExperiment: SummarizedExperiment container. R package version 1.26.1, https://bioconductor.org/packages/SummarizedExperiment

Examples

library(scran); library(scuttle); library(SummarizedExperiment) 
sce <- mockSCE()
sce.qc <- qc_cell(sce, qc.metric=list(subsets=list(Mt=rowData(sce)$featureType=='mito'), threshold=1))
sce.norm <- norm_cell(sce.qc)

jianhaizhang/spatialHeatmap documentation built on Nov. 28, 2024, 4:44 p.m.