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 data

We obtain a single-cell RNA sequencing dataset of Olfactory Epithelium cells from multiple mice from @fletcher2017deconstructing. Counts for the endogenous genes, spike-ins, and gene constructs are available from the Gene Expression Omnibus using the accession number GSE95601. We download and cache them using the r Biocpkg("BiocFileCache") package.

library(BiocFileCache)
bfc <- BiocFileCache("raw_data", ask = FALSE)

fname <- bfcrpath(bfc, "https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE95601&format=file&file=GSE95601%5FoeHBCdiff%5FCufflinks%5FeSet%5Fcounts%5Ftable%2Etxt%2Egz")

protocol_data_file <- bfcrpath(bfc, "https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE95601&format=file&file=GSE95601%5FoeHBCdiff%5FCufflinks%5FeSet%5FprotocolData%2Etxt%2Egz")

pheno_data_file <- bfcrpath(bfc, "https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE95601&format=file&file=GSE95601%5FoeHBCdiff%5FphenoData%2Etxt%2Egz")

rowdata_file <- bfcrpath(bfc, "https://www.ncbi.nlm.nih.gov/geo/download/?acc=GSE95601&format=file&file=GSE95601%5FoeHBCdiff%5FCufflinks%5FeSet%5FfeatureData%2Etxt%2Egz")

Reading the counts in a matrix and the row and column data in dataframes:

library(dplyr)

counts <- read.table(fname)
counts <- as.matrix(counts)

protocol_data <- read.table(protocol_data_file, header = TRUE)
pheno_data <- read.table(pheno_data_file, header = TRUE)
coldata <- inner_join(pheno_data, protocol_data, by = "sample_sequencing_id")

rowdata <- read.table(rowdata_file, header = TRUE)

Attaching the cluster results from the original analysis (cluster labels available here):

cluster_file <- bfcrpath(bfc, "https://raw.githubusercontent.com/rufletch/p63-HBC-diff/master/ref/oeHBCdiff_clusterLabels.txt")
cluster_id <- read.table(cluster_file, col.names = c("sample_id", "cluster_id"))

cluster_labels <- data.frame(cluster_id = c(1:5, 7:12, 14, 15),
                             cluster_label = c("HBC", 
                                       "INP1", 
                                       "GBC", 
                                       "mSUS", 
                                       "HBC2", 
                                       "iSUS", 
                                       "HBC1", 
                                       "iOSN", 
                                       "INP3", 
                                       "MVC1", 
                                       "mOSN", 
                                       "INP2", 
                                       "MVC2"),
                             cluster_description = c("Resting Horizontal Basal Cells", 
                                             "Immediate Neuronal Precursor 1", 
                                             "Globose Basal Cells", 
                                             "Mature Sustentacular Cells", 
                                             "Transitional HBC 2", 
                                             "Immature Sustentacular Cells", 
                                             "Transitional HBC 1", 
                                             "Immature Olfactory Sensory Neurons", 
                                             "Immediate Neuronal Precursor 3", 
                                             "Microvillous Cells, type 1", 
                                             "Mature Olfactory Sensory Neurons", 
                                             "Immediate Neuronal Precursor 2", 
                                             "Microvillous Cells, type 2"))

cluster_anno <- left_join(cluster_id, cluster_labels, by = "cluster_id")
full_coldata <- left_join(coldata, cluster_anno, 
                          by = c("sample_sequencing_id"="sample_id"))

Creating a SingleCellExperiment object:

library(SingleCellExperiment)
sce <- SingleCellExperiment(list(counts=counts),
                            colData = full_coldata, rowData = rowdata)

Saving to file

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

path <- file.path("scRNAseq", "fletcher-olfactory", "2.6.0")
dir.create(path, showWarnings=FALSE, recursive=TRUE)
saveRDS(assay(sce), file=file.path(path, "counts.rds"))
saveRDS(colData(sce), file=file.path(path, "coldata.rds"))
saveRDS(rowData(sce), file=file.path(path, "rowdata.rds"))