In drisso/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 the mouse brain from @usoskin2015unbiased. RPMs for endogenous genes and repeat regions are available as External Resource Table 1 at http://linnarssonlab.org/drg/. We download and cache them using the r Biocpkg("BiocFileCache") package.

library(BiocFileCache)
bfc <- BiocFileCache("raw_data", ask = FALSE)
base.url <- file.path("https://storage.googleapis.com",
    "linnarsson-lab-www-blobs/blobs/drg")
count.file <- bfcrpath(bfc, file.path(base.url,
    "Usoskin%20et%20al.%20External%20resources%20Table%201.xlsx"))

We load them into memory.

library(readxl)
all.raw <- read_xlsx(count.file, sheet=2, col_names=FALSE)

Unpacking the format

We need to unpack the column data:

meta.raw <- head(all.raw, 10)
coldata <- data.frame(t(meta.raw[,-(1:9)]), stringsAsFactors=FALSE)

library(S4Vectors)
coldata <- DataFrame(coldata)
colnames(coldata) <- meta.raw[,9,drop=TRUE]
rownames(coldata) <- NULL

coldata[,5] <- as.numeric(coldata[,5])
coldata

And then the rowdata:

gene.info <- tail(all.raw, -11)
rowdata <- as.data.frame(gene.info[,1:8])
rowdata.names <- all.raw[11,1:8,drop=TRUE]
rowdata.names <- sub("^[0-9]\\. ", "", rowdata.names)
rowdata <- DataFrame(rowdata)
colnames(rowdata) <- rowdata.names
rowdata

And finally, the RPMs (since no raw counts have been provided):

rpms <- as.matrix(gene.info[,-(1:9)])
storage.mode(rpms) <- "numeric"
colnames(rpms) <- NULL
dim(rpms)

Saving to file

We now save all of the components to file for upload to r Biocpkg("ExperimentHub"). These will be used to construct a SingleCellExperiment on the client side when the dataset is requested.

path <- file.path("scRNAseq", "usoskin-brain", "2.0.0")
dir.create(path, showWarnings=FALSE, recursive=TRUE)
saveRDS(rpms, file=file.path(path, "rpms.rds"))
saveRDS(coldata, file=file.path(path, "coldata.rds"))
saveRDS(rowdata, file=file.path(path, "rowdata.rds"))