integrateWithSingleCell {DESeq2} | R Documentation

## Integrate bulk DE results with Bioconductor single-cell RNA-seq datasets

### Description

A function that assists with integration of bulk DE results tables with pre-processed scRNA-seq datasets available on Bioconductor, for downstream visualization tasks. The user is prompted to pick a scRNA-seq dataset from a menu. The output of the function is a list with the original results table, bulk gene counts, and the SingleCellExperiment object selected by the user.

### Usage

    integrateWithSingleCell(res, dds, ...)

### Arguments

`res` | a results table, as produced via `results`
`dds` | a DESeqDataSet with the bulk gene expression data (should contain gene-level counts)
`...` | additional arguments passed to the dataset-accessing function

### Details

This function assists the user in choosing a datset from a menu of options that are selected based on the organism of the current dataset. Currently only human and mouse bulk and single-cell RNA-seq datasets are supported, and it is assumed that the bulk DE dataset has GENCODE or Ensembl gene identifiers. Following the selection of the scRNA-seq dataset, visualization can be performed with a package `vizWithSCE`, which can be installed with `install_github("KwameForbes/vizWithSCE")`.

### Value

list containing: res, dds, and a SingleCellExperiment as selected by the user

### Author(s)

Kwame Forbes

### Examples

    ## Not run:
      # involves interactive menu selection...
      dds <- makeExampleDESeqDataSet()
      rownames(dds) <- paste0("ENSG",1:nrow(dds))
      dds <- DESeq(dds)
      res <- results(dds)
      dat <- integrateWithSingleCell(res, dds)

    ## End(Not run)

[Package DESeq2 version 1.32.0 Index]