norm_cell: Normalizing single cell data
In jianhaizhang/spatialHeatmap: spatialHeatmap

norm_cell

R Documentation

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 jzhan067@ucr.edu
Dr. Thomas Girke thomas.girke@ucr.edu

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 April 21, 2024, 7:43 a.m.