const-ae / highlyreplicatedrnaseq

Collection of Bulk RNA-Seq Experiments With Many Replicates

HighlyReplicatedRNASeq

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.

Installation

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")

Datasets

• Schurch et al. (2016): 86 samples of S. cerevisiae in two conditions
  • Schurch16() / Schurch16_metadata()

At the moment, this package contains only one dataset, but more datasets can be added in the future.

Example

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

References

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