se_to_matrix: SummarizedExperiment to matrix

In federicomarini/quantiseqr: Quantification of the Tumor Immune contexture from RNA-seq data

SummarizedExperiment to matrix

Description

SummarizedExperiment to matrix

Usage

se_to_matrix(se, assay = "abundance")

Arguments

se	A SummarizedExperiment object, or any of its derivates, which contains the information on the TPM expression values, which are stored in a specified assay slot.
assay	A character string, specifying the name of the assays component of the se object. Defaults to "abundance", as this is the common convention used e.g. by the tximport package to store the values imported from the transcript level quantifications

Value

A matrix object, containing the TPM values, ready to be used in the framework of quantiseqr

Examples

library("SummarizedExperiment")
library("macrophage")
data("gse", package = "macrophage")
se <- gse

# If using ENSEMBL or Gencode gene annotation, you might want to convert the row names
## in this case, the gene symbols are provided as rowData information
rownames(se) <- rowData(se)$SYMBOL

tpm_matrix <- se_to_matrix(se, assay = "abundance")

## otherwise, you can map the identifiers via
library("org.Hs.eg.db")
library("AnnotationDbi")
se <- gse
# keep the parts before the '.', used in the Gencode annotation
rownames(se) <- substr(rownames(se), 1, 15)
gene_names <- mapIds(org.Hs.eg.db,
                     keys = rownames(se),
                     column = "SYMBOL",
                     keytype = "ENSEMBL")
rownames(se) <- gene_names

# If you require to convert the counts to TPMs by hand, you need a vector of
# gene lengths as well, and then run this simple function on the count matrix
counts_to_tpm <- function(counts, lengths) {
  ratio <- counts / lengths
  mytpm <- ratio / sum(ratio) * 1e6
  return(mytpm)
}
# then run via
# tpmdata <- counts_to_tpm(count_matrix, genelength_vector)

federicomarini/quantiseqr documentation built on Dec. 20, 2024, 2:39 a.m.