In LTLA/scRNAseq: Collection of Public Single-Cell RNA-Seq Datasets

library(BiocStyle)
knitr::opts_chunk$set(error=FALSE, message=FALSE, warning=FALSE)

Downloading the count data

We obtain a single-cell RNA sequencing dataset of mouse ESCs from Leng et al. (2015).

library(GEOquery)
tmp <- "geo_cache"
if (!file.exists(tmp)) {
    dir.create(tmp)
    out <- getGEOSuppFiles("GSE64016", baseDir=tmp)
}
rownames(out)

Processing the read counts

We read in the count matrix for cells in each cell cycle phase.

count.file <- rownames(out)[1]
hs.counts <- read.csv(count.file, header=TRUE, row.names=1)
hs.counts <- as.matrix(hs.counts)
dim(hs.counts)

Creating column metadata

Pulling information out of GSE64016's description.

cellline <- rep(c("H1", "H1-Fucci"), c(213, 247))
experiment <- sub(".*_Exp([0-9]+)\\..*", "\\1", colnames(hs.counts))
phase <- sub("_Exp.*", "", colnames(hs.counts))
phase[!phase %in% c("G1", "S", "G2M")] <- NA

library(S4Vectors)
coldata <- DataFrame(CellLine=cellline, Experiment=experiment, Phase=phase)
coldata

Saving for upload

Forming a SingleCellExperiment:

library(SingleCellExperiment)
sce <- SingleCellExperiment(list(normalized=hs.counts), colData=coldata)

Doing some polishing to save space:

library(scRNAseq)
sce <- polishDataset(sce)
sce

We save this to disk in preparation for upload:

meta <- list(
    title="Oscope identifies oscillatory genes in unsynchronized single-cell RNA-seq experiments",
    description="Oscillatory gene expression is fundamental to development, but technologies for monitoring expression oscillations are limited. We have developed a statistical approach called Oscope to identify and characterize the transcriptional dynamics of oscillating genes in single-cell RNA-seq data from an unsynchronized cell population. Applying Oscope to a number of data sets, we demonstrated its utility and also identified a potential artifact in the Fluidigm C1 platform.",
    taxonomy_id="9606",
    genome="GRCh37",
    sources=list(
        list(provider="GEO", id="GSE64016"),
        list(provider="PubMed", id="26301841")
    ),
    maintainer_name="Aaron Lun",
    maintainer_email="[e-mail]"
)

saveDataset(sce, "2023-12-18_output", meta)

Session information {-}

sessionInfo()

LTLA/scRNAseq documentation built on April 29, 2024, 12:34 p.m.