se_to_matrix.RdSummarizedExperiment to matrix
se_to_matrix(se, assay = "abundance")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.
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
A matrix object, containing the TPM values, ready to be used in the
framework of quantiseqr
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")
#> Loading required package: AnnotationDbi
#>
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")
#> 'select()' returned 1:many mapping between keys and columns
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)