Collection of Bulk RNA-Seq Experiments With Many Replicates
The HighlyReplicatedRNASeq package provides access to the count matrix results from studies with many replicates. These datasets can be valuable for benchmarking tools designed to handle RNA-seq data.
You can install the latest version of HighlyReplicatedRNASeq with
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("HighlyReplicatedRNASeq")
To get the latest development version, install the package from Github
# install.packages("devtools")
devtools::install_github("const-ae/HighlyReplicatedRNASeq")
Schurch16()
/ Schurch16_metadata()
At the moment, this package contains only one dataset, but more datasets can be added in the future.
Load the Schurch16
dataset by calling the corresponding function. The
first time you run this command, it will download the dataset and will
subsequently cache it in a directory that is by
getExperimentHubOption("CACHE")
.
schurch_se <- HighlyReplicatedRNASeq::Schurch16()
#> snapshotDate(): 2020-03-24
#> see ?HighlyReplicatedRNASeq and browseVignettes('HighlyReplicatedRNASeq') for documentation
#> loading from cache
schurch_se
#> class: SummarizedExperiment
#> dim: 7126 86
#> metadata(0):
#> assays(1): counts
#> rownames(7126): 15S_rRNA 21S_rRNA ... tY(GUA)O tY(GUA)Q
#> rowData names(0):
#> colnames(86): wildtype_01 wildtype_02 ... knockout_47 knockout_48
#> colData names(4): file_name condition replicate name
Schurch, N. J., Schofield, P., Gierliński, M., Cole, C., Sherstnev, A., Singh, V., … Barton, G. J. (2016). How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use? , 22(6), 839–851. https://doi.org/10.1261/rna.053959.115
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