The ProbMatrixCellTypes class is a data storage class that contains
information related to the cell composition matrices used for the simulation
of pseudo-bulk RNA-Seq samples. The matrix is stored in the
prob.matrix
slot. The other of slots contain additional information
generated during the process and required in subsequent steps.
As described in Torroja and Sanchez-Cabo, 2019, the proportions are
constructed using six different methods in order to avoid biases due to the
composition of the simulated bulk samples. In plots
slot, plots are
stored that visually represent the distribution of these probabilities in
order to provide a way to monitor the different sets of samples generated.
These plots can be shown using the showProbPlot
function (see
?showProbPlot
for more details).
prob.matrix
Matrix of cell proportions generated for the simulation of bulk samples. Rows correspond to the bulk samples to be generated (\(i\)), columns are the cell types present in the provided single-cell data (\(j\)) and each entry is the proportion of \(j\) cell type in \(i\) sample.
cell.names
Matrix containing the names of the cells that will make up each simulated pseudo-bulk sample.
set.list
List of cells sorted according to the cell type they belong to.
set
Vector containing the cell names present in the object.
plots
List of lists with plots showing the distribution of the cell
proportions generated by each method during the process. In each list,
boxplot
, violinplot
, linesplot
or ncelltypes
can be found. Please see showProbPlot
for more details.
type.data
Character with the type of data contained: training or test.
Torroja, C. and Sánchez-Cabo, F. (2019). digitalDLSorter: A Deep Learning algorithm to quantify immune cell populations based on scRNA-Seq data. Frontiers in Genetics 10, 978. doi: doi:10.3389/fgene.2019.00978