View source: R/activityScores.R
normalize_gene_activities | R Documentation |
Normalize the output of build_gene_activity_matrix
. Input is
either one or multiple gene activity matrices. Any gene activities to be
compared amongst each other should be normalized together.
normalize_gene_activities(activity_matrices, cell_num_genes)
activity_matrices |
A gene activity matrix, output from
|
cell_num_genes |
A named vector of the total number of accessible sites per cell. Names should correspond to the cell names in the activity matrices. These values can be found in the "num_genes_expressed" column of the pData table of the CDS used to calculate the gene activity matrix. |
Normalized activity matrix or matrices.
data("cicero_data") data("human.hg19.genome") sample_genome <- subset(human.hg19.genome, V1 == "chr18") sample_genome$V2[1] <- 100000 input_cds <- make_atac_cds(cicero_data, binarize = TRUE) input_cds <- detectGenes(input_cds) input_cds <- reduceDimension(input_cds, max_components = 2, num_dim=6, reduction_method = 'tSNE', norm_method = "none") tsne_coords <- t(reducedDimA(input_cds)) row.names(tsne_coords) <- row.names(pData(input_cds)) cicero_cds <- make_cicero_cds(input_cds, reduced_coordinates = tsne_coords) cons <- run_cicero(cicero_cds, sample_genome, sample_num=2) data(gene_annotation_sample) gene_annotation_sub <- gene_annotation_sample[,c(1:3, 8)] names(gene_annotation_sub)[4] <- "gene" input_cds <- annotate_cds_by_site(input_cds, gene_annotation_sub) num_genes <- pData(input_cds)$num_genes_expressed names(num_genes) <- row.names(pData(input_cds)) unnorm_ga <- build_gene_activity_matrix(input_cds, cons) cicero_gene_activities <- normalize_gene_activities(unnorm_ga, num_genes)
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