Produce a weitrix of proportions within groups — counts

Produce a weitrix of proportions between 0 and 1. The input is read counts at a collection of features in a collection of samples. The features need to be grouped, for example by gene. The proportions will add to 1 within each group.

counts_proportions(counts, grouping, verbose = TRUE, typecast = identity)

Arguments

counts	A matrix of read counts. Rows are peaks and columns are samples.
grouping	A data frame defining the grouping of features. Should have a column "group" naming the group and a column "name" naming the feature (corresponding to `rownames(counts)`).
verbose	If TRUE, output some debugging and progress information.
typecast	A function to convert a matrix to a matrix-like type. Applied at the chunk level, before all chunks are `rbind`ed. Allows use of memory-efficient matrix representations.

Value

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

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_proportions(counts, grouping)
#> Calculating proportions in 1 blocks

weitrix_x(wei)
#>    [,1]      [,2] [,3]
#> p1  0.5 0.6666667   NA
#> p2  0.0 0.3333333   NA
#> p3  0.5 0.0000000   NA
#> p4   NA 0.0000000  0.5
#> p5   NA 1.0000000  0.5
weitrix_weights(wei)
#>    [,1] [,2] [,3]
#> p1    2    3    0
#> p2    2    3    0
#> p3    2    3    0
#> p4    0    2    2
#> p5    0    2    2
rowData(wei)
#> DataFrame with 5 rows and 3 columns
#>          group total_reads per_read_var
#>    <character>   <numeric>    <numeric>
#> p1           A           5       0.2400
#> p2           A           5       0.1600
#> p3           A           5       0.1600
#> p4           B           4       0.1875
#> p5           B           4       0.1875