Dino_SCE: Run Dino normalization on a SingleCellExperiment dataset

In JBrownBiostat/Dino: Normalization of Single-Cell mRNA Sequencing Data

Run Dino normalization on a SingleCellExperiment dataset

Description

Dino_SCE is a wrapper simplifying the application of the Dino method to data formatted as a SingleCellExperiment

Usage

Dino_SCE(SCE, ...)

Arguments

SCE	A SingleCellExperiment object with unnormalized count data (eg. raw UMIs) in the assays slot under the name counts.
...	Further arguments to pass to Dino

Value

Dino_SCE returns a SingleCellExperiment object using Dino normalized expression in the assays slot under the normcounts name for downstream analysis.

If returnMeta = T is passed to Dino, then depth and slope results are stored in the metadata slot under the names depth and slope respectively.

Author(s)

Jared Brown

References

Brown, J., Ni, Z., Mohanty, C., Bacher, R. and Kendziorski, C. (2020). "Normalization by distributional resampling of high throughput single-cell RNA-sequencing data." bioRxiv. https://doi.org/10.1101/2020.10.28.359901

Amezquita, R.A., Lun, A.T.L., Becht, E., Carey, V.J., Carpp, L.N., Geistlinger, L., Marini, F., Rue-Albrecht, K., Risso, D., Soneson, C., et al. (2020). "Orchestrating single-cell analysis with Bioconductor." Nat. Methods, 17, 137–145. https://doi.org/10.1038/s41592-019-0654-x

Examples

# raw data
data("pbmcSmall")
str(pbmcSmall)

# format as SingleCellExperiment
library(SingleCellExperiment)
pbmc_SCE <- SingleCellExperiment(assays = list("counts" = pbmcSmall))

# Run Dino
pbmc_SCE <- Dino_SCE(pbmc_SCE)
str(pbmc_SCE)
str(normcounts(pbmc_SCE))

JBrownBiostat/Dino documentation built on June 11, 2022, 1:27 p.m.