heatmap_data_BUSseq {BUSseq} | R Documentation

## Draw the Heatmap of the Log-scale Read Count Data for the Output of the `BUSseq_MCMC` Function

### Description

Plot the heatmap of the log-scale read count data across multiple batches, and then save the resulting images in the user's directory as "png" format.

### Usage

    heatmap_data_BUSseq(sce_BUSseqfit,
                        data_type = c("Raw","Imputed","Corrected"),
                        gene_set = NULL,
                        project_name= paste0("BUSseq_heatmap_",data_type),
                        image_dir = NULL, color_key_seq = NULL,
                        image_width = 1440, image_height = 1080)

### Arguments

`sce_BUSseqfit` | An output `SingleCellExperiment` object obtained from the function `BUSseq_MCMC`.
`data_type` | A string to determine which count data matrix is used to draw the heatmap, "Raw" for the raw count data, "Imputed" for the imputed data, and "Corrected" for the corrected data.
`gene_set` | A vector of gene indices indicating the gene set of interest to display in the heatmap. The default is all genes. We also recommend displaying the intrinsic genes obtained from `intrisic_genes_BUSseq(BUSseqfits_obj)`.
`project_name` | A string to name the "png" image. By default, the figure is named as "BUSseq_heatmap_Raw_log1p_data.png."
`image_dir` | A directory to store the gnereated heatmap. The default is to create a folder called "image" in the current directory and save there.
`color_key_seq` | A numeric vector indicating the splitting points for binning log-scale read counts into colors. The default is to space the color key points equally between the minimum and maximum of the log-scale read count data.
`image_width` | The width in pixels of the graphical device to plot. The default is 1440 px.
`image_height` | The height in pixels of the graphical device to plot. The default is 1080 px.

### Details

To cope with the zeros in the count data, we take the transformation log(1+x) on all count data, which corresponds to the R function `log1p()` instead of `log()`.

### Value

Visualize the gene expression data matrix, where each row represents a gene, and each column represents a sample.

### Author(s)

Fangda Song

### References

Song, Fangda, Ga Ming Angus Chan, and Yingying Wei. Flexible experimental designs for valid single-cell RNA-sequencing experiments allowing batch effects correction. Nature communications 11, no. 1 (2020): 1-15.

### Examples

      library(SingleCellExperiment)
      # Plot the imputed read count data of the first 100 genes
      heatmap_data_BUSseq(BUSseqfits_example, data_type = "Imputed",
                          gene_set = 1:100)

[Package BUSseq version 1.0.0 Index]