countsimQC is an R package that provides functionality to create a
comprehensive report comparing many different characteristics across multiple
count data sets. One important use case is comparing one or more
synthetic (e.g., RNA-seq) count matrices to a real count matrix, possibly the
one based on which the synthetic data sets were generated. However, any
collection of one or more count matrices can be visualized and compared.
If you use
countsimQC for your work, we appreciate if you cite the
countsimQC can be installed from
Bioconductor with the
following commands. Note that R version >= 3.5 and Bioconductor
version >= 3.8 are required in order to use the
If you have an older version of R (3.4), you can still install
countsimQC v0.5.4 (see the
Releases tab in the GitHub repository).
Please see the
NEWS file for differences between versions.
## Install `BiocManager` if needed if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") ## Install countsimQC BiocManager::install("countsimQC")
countsimQC and generate a report, you simply need to call the
countsimQCReport(), with an input consisting of a named list of
DESeqDataSets (see the
package for a description of this class). Each
correspond to one data set and contain a count matrix, a data frame with sample
information and a design formula, which is needed for proper dispersion
calculations. To generate a
DESeqDataSet from a count matrix
sample information data frame
sample_df and a design formula
(of the form
~ predictors), you can do as follows:
library(DESeq2) dds <- DESeqDataSetFromMatrix(countData = counts, colData = sample_df, design = formula)
There are many other ways of generating valid
DESeqDataSets, depending on in
what form your counts are (e.g., reading directly from
HTSeq output, or from a tximport
output object (see the
countsimQC contains an small example list with subsets of three data sets:
two synthetic ones and the real data set that was used to generate them. The
following code generates a comparative report for these three data sets:
library(countsimQC) data(countsimExample) countsimQCReport(ddsList = countsimExample, outputFile = "countsimReport.html", outputDir = "./", description = "This is a comparison of three count data sets.")
For more detailed information about how to use the package, we refer to the vignette:
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