Produce a weitrix of shift scores between -1 and 1. The input is read counts at a collection of peaks (or other features) in a collection of samples. The peaks can be grouped by gene, and are ordered within each gene.

counts_shift(counts, grouping, verbose = TRUE)

Arguments

counts

A matrix of read counts. Rows are peaks and columns are samples.

grouping

A data frame defining the grouping of peaks into genes. Should have a column "group" naming the gene and a column "name" naming the peak (corresponding to rownames(counts)). Within each group, peak names should be ordered from 5' to 3' position.

verbose

If TRUE, output some debugging and progress information.

Value

A SummarizedExperiment object with metadata fields marking it as a weitrix.

Details

For a particular gene, a shift score measures measures the tendency of reads to be upstrand (negative) or downstrand (positive) of the average over all samples. Shift scores range between -1 and 1.

Examples

grouping <- data.frame( group=c("A","A","A","B","B"), name=c("p1","p2","p3","p4","p5")) counts <- rbind( p1=c(1,2,0), p2=c(0,1,0), p3=c(1,0,0), p4=c(0,0,1), p5=c(0,2,1)) wei <- counts_shift(counts, grouping)
#> Calculating shifts in 1 blocks
weitrix_x(wei)
#> [,1] [,2] [,3] #> A 0.2 -0.1333333 NA #> B NA 0.2500000 -0.25
#> [,1] [,2] [,3] #> A 2 3 0 #> B 0 2 2
rowData(wei)
#> DataFrame with 2 rows and 2 columns #> per_read_var total_reads #> <numeric> <numeric> #> A 0.2560 5 #> B 0.1875 4