Perform DGE analysis

Perform differential gene expression analysis with DESeq2

run_deseq2(
  counts,
  pd,
  id_col = NULL,
  cond_col,
  cond_levels = NULL,
  lfc_threshold = 0,
  sig_threshold = 0.01,
  dge_calling_strategy = "bulk",
  subset_feature = NULL,
  subset_sample = NULL,
  deseq_opts = list(),
  lfc_shrink_opts = list(),
  return_dds = FALSE,
  BPPARAM = BiocParallel::SerialParam()
)

Arguments

counts	Can be either: (sparse) matrix with gene counts, where the rows correspond to genes. One column per sample/cell with the count data for the specified genes must be present (The names of these columns must match with the identifiers in id_col). An results object from tximport (preferred if import_dge_counts() was used with bulk data). Seurat object with a gene level assay as active.assay (most likely result object from combine_to_matrix())
pd	Data frame with at least a column of sample/cell identifiers (rownames or specified in id_col) and the comparison group definition (specified in cond_col).
id_col	Name of the column in pd, where unique sample/cell identifiers are stored. If NULL (default), use rownames of pd.
cond_col	Name of the column in pd, where the comparison groups/conditions are defined. If more than 2 levels/groups are present, the groups that should be used must be specified in cond_levels.
cond_levels	Define two levels/groups of cond_col, that should be compared. The order of the levels states the comparison formula (i.e. cond_col[1]-cond_col[2]).
lfc_threshold	Specify a log2 fold change threshold (on log2 scale) to test against. 0 implicates no threshold.
sig_threshold	Specify a significance threshold for the results adjusted p-values or s-values. 1 implicates no threshold.
dge_calling_strategy	Should be either 'bulk' or 'sc'. Specify the type of the provided data (bulk or single-cell RNA-seq) so that appropriate parameters can be applied.
subset_feature	Subsets the provided count matrix to only specified features. Can be names, indices or logicals.
subset_sample	Subsets the provided count matrix to only specified samples. Can be names, indices or logicals.
deseq_opts	Manually specify parameters for the DESeq function. Will overwrite recommended parameters if necessary.
lfc_shrink_opts	Manually specify parameters for the lfcShrink function. Will overwrite recommended parameters if necessary.
return_dds	Should the DESeqDataSet object be returned?
BPPARAM	If multicore processing should be used, specify a BiocParallelParam object here. Among others, can be SerialParam() (default) for non-multicore processing or MulticoreParam('number_cores') for multicore processing. See BiocParallel for more information.

Value

A list with the analysis results and parameters:

• results_all: Data frame of the DGE test results for all analyzed genes.

• results_sig: Data frame of the significant DEG test results, according to the specified parameters (sig_threshold, lfc_threshold).

• dds: The DESeqDataSet of the analysis, if return_dds=TRUE.

• drim: Results of the DRIMSeq statistical computations (dmTest()).

• sval_threshold / adjp_threshold: The given significance threshold used to either filter s-values or adjusted p-values.

• comparison: A string representation of the performed comparison.

• condition1: The first condition of the performed comparison.

• condition2: The second condition of the performed comparison.

• sample_table: The (filtered) sample table (pd) - including the condition column used for comparison.

• deseq_opts: A list of used DESeq parameters.

• lfc_shrink_opts: A list of used lfcShrink parameters.

Details

Offers functionality to perform a DGE analysis for bulk and single-cell data with DESeq2, automatically applying recommended models and parameter settings. It is strongly advised to provide 'raw' count data, as imported with import_dge_counts(). Installation of package 'apeglm' is recommended for LFC-shrinkage, for single-cell data the package 'glmGamPoi' is additionally recommended. For questions about DESeq2, LFC-shrinkage or s-values, please refer to the excellent DESeq2 vignette.

See also

import_dge_counts() for correct import of gene-level counts. combine_to_matrix() to summarize scRNA counts to one matrix.

Other DTUrtle DGE: import_dge_counts()