se_to_matrix {quantiseqr} | R Documentation |
SummarizedExperiment to matrix
se_to_matrix(se, assay = "abundance")
se |
A |
assay |
A character string, specifying the name of the |
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") 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)