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.

Details

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).

Slots

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.

References

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