Construct a metaXpressStudy

Builds a metaXpressStudy from a count matrix and a sample metadata table.

Usage

metaXpressStudy(
  counts = matrix(0L, nrow = 0, ncol = 0),
  metadata = data.frame(),
  accession = character(0),
  organism = "Homo sapiens",
  qc_score = NA_real_,
  de_result = data.frame(),
  gene_info = NULL
)

Arguments

counts

A numeric matrix of raw counts (genes x samples). Rownames must be gene identifiers; colnames must be sample identifiers.

metadata

A data.frame of sample metadata, one row per column of counts. Must contain a condition column when accession is set.

accession

A length-1 character accession ID, or "local".

organism

A length-1 character species name.

qc_score

A length-1 numeric QC score, NA if not yet run.

de_result

A data.frame of DE results (usually empty).

gene_info

Optional data.frame or DataFrame of gene annotation, one row per row of counts; stored as rowData.

Value

A metaXpressStudy object.

Examples

counts <- matrix(rpois(24, 100), nrow = 4,
                 dimnames = list(paste0("GENE", 1:4), paste0("S", 1:6)))
meta <- data.frame(sample_id = paste0("S", 1:6),
                   condition = rep(c("control", "case"), each = 3))
study <- metaXpressStudy(counts, meta, accession = "local")
study
#> metaXpressStudy
#>   Accession : local 
#>   Organism  : Homo sapiens 
#>   Genes     : 4 
#>   Samples   : 6 
#>   QC score  : not run 
#>   DE run    : FALSE