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 data

We obtain a single-cell RNA sequencing dataset of human radial glial cells from Pollen et al. (2015). Counts for endogenous genes are available from Dropbox (why would you do that!?) via https://www.pollenlab.org/datasets.

library(BiocFileCache)
bfc <- BiocFileCache("raw_data", ask = FALSE)
exprs.path <- bfcrpath(bfc, "https://www.dropbox.com/s/rjrkq96li4j4rvn/oRG%20paper%20-%20counts.txt?dl=1")

library(scuttle)
mat <- readSparseCounts(exprs.path, row.names=1)
dim(mat)
str(dimnames(mat))

We also read in the per-cell metadata from an Excel file (why!?).

meta.path <- bfcrpath(bfc, "https://www.dropbox.com/s/rb9tl4gjswrxfy9/Pollen%20et%20al%202015%20updated%20metadata.xlsx?dl=1")

library(readxl)
meta <- DataFrame(read_excel(meta.path), check.names=FALSE)
meta$`AlignmentRate, Pairs` <- as.numeric(sub("%$", "", meta$`AlignmentRate, Pairs`))/100

rownames(meta) <- meta$Cell
meta$Cell <- NULL # redundant with the row names.
stopifnot(all(colnames(mat) %in% rownames(meta)))

meta <- meta[colnames(mat),]
meta

Saving to file

Making sure we can assemble the final SCE:

sce <- SingleCellExperiment(list(counts=mat), colData=meta)

Applying some polish to optimize for disk space:

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

We now save all of the relevant components to file for upload to r Biocpkg("ExperimentHub").

meta <- list(
    title="Molecular identity of human outer radial glia during cortical development",
    description="Radial glia, the neural stem cells of the neocortex, are located in two niches: the ventricular zone and outer subventricular zone. Although outer subventricular zone radial glia may generate the majority of human cortical neurons, their molecular features remain elusive. By analyzing gene expression across single cells, we find that outer radial glia preferentially express genes related to extracellular matrix formation, migration, and stemness, including TNC, PTPRZ1, FAM107A, HOPX, and LIFR. Using dynamic imaging, immunostaining, and clonal analysis, we relate these molecular features to distinctive behaviors of outer radial glia, demonstrate the necessity of STAT3 signaling for their cell cycle progression, and establish their extensive proliferative potential. These results suggest that outer radial glia directly support the subventricular niche through local production of growth factors, potentiation of growth factor signals by extracellular matrix proteins, and activation of self-renewal pathways, thereby enabling the developmental and evolutionary expansion of the human neocortex.",
    taxonomy_id="9606",
    genome="GRCh37",
    sources=list(
        list(provider="URL", id="https://www.pollenlab.org/datasets", version=as.character(Sys.Date())),
        list(provider="PubMed", id="26406371")
    ),
    maintainer_name="Aaron Lun",
    maintainer_email="[e-mail]"
)

saveDataset(sce, "2023-12-22_output", meta)

Session information {-}

sessionInfo()

LTLA/scRNAseq documentation built on June 28, 2024, 7:31 p.m.