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Bulk RNAseq differential gene expression class

BulkDge.Rd

Class for coordinating differential gene expression analyses with subsequent GSE in a structured format. The filtered counts, library sizes and normalisation factors are stored in the class; get_dge_list() turns them into an edgeR DGEList on demand.

Usage

BulkDge(
  raw_counts,
  meta_data,
  variable_info = NULL,
  alternative_gene_id = NULL
)

Arguments

raw_counts

matrix. The raw count matrix. Rows = genes, columns = samples. Note: this is different from the BulkCoExp() class!

meta_data

data.table. Metadata information on the samples. It expects to have a column sample_id and case_control column.

variable_info

data.table. Metadata information on the features. This is an optional table. Defaults to NULL.

alternative_gene_id

String. Optional alternative gene identifier to be used. Must be a column of variable_info!

Value

Returns the BulkDge class for further operations.

Properties

raw_counts

A numerical matrix of the provided raw data.

meta_data

A data.table with the meta-information about the samples.

variable_info

An optional data.table containing the variable info.

outputs

A list in which key outputs will be stored.

plots

A list with the plots that are generated during subsequent QC steps.

params

A (nested) list that will store all the parameters of the applied function.

final_results

A list in which final results will be stored.

Examples

# DGE class over synthetic bulk counts (genes x samples)
syn <- synthetic_bulk_cor_matrix()
meta <- data.table::data.table(
  sample_id = colnames(syn$counts),
  case_control = rep(c("case", "control"), each = 50)
)
object <- BulkDge(raw_counts = syn$counts, meta_data = meta)
object
#> Bulk differential gene expression class (BulkDge).
#>  Raw counts: 1000 genes x 100 samples.
#>  Meta-data rows: 100.
#>  Variable info provided: FALSE.
#>  Applied steps:
#>   qc_bulk_dge(): FALSE.
#>   normalise_bulk_dge(): FALSE.
#>   batch_correction_bulk_dge(): FALSE.
#>   calculate_pca_bulk_dge(): FALSE.
#>   calculate_dge_limma(): FALSE.
#>   calculate_dge_hedges(): FALSE.
#>   TPM normalisation: FALSE.
#>   FPKM normalisation: FALSE.