COMPASSContainer: Generate the Data Object used by COMPASS
In RGLab/COMPASS: Combinatorial Polyfunctionality Analysis of Single Cells

Description Usage Arguments Details Value Examples

This function generates the data container suitable for use with COMPASS.

COMPASSContainer(
  data,
  counts,
  meta,
  individual_id,
  sample_id,
  countFilterThreshold = 0
)

`data`	A list of matrices. Each matrix `M_i` is made up of `N_i` cells by `K` markers; for example, it could be the intensity information from an intracellular cytokine experiment. Each element of the list should be named; this name denotes which sample the cell intensities were measured from.
`counts`	A named integer vector of the cell counts(of the parent population) for each sample in `data`.
`meta`	A `data.frame` of metadata, describing the individuals in the experiment. Each row in `meta` should correspond to a row in `data`. There should be one row for each sample; i.e., one row for each element of `data`.
`individual_id`	The name of the vector in `meta` that denotes the individuals from which samples were drawn. In this sense an individual equates to a single subject, or person.
`sample_id`	The name of the vector in `meta` that denotes the samples. The sample_id identifies a combination of a subject with visit (if any), cell subset measured (e.g. CD4), and stimulation. This vector should contain all of the names in the `data` input.
`countFilterThreshold`	Numeric; if the number of parent cells is less than this threshold, we remove that file. Default is 0, which means filter is disabled.

The names attributes for the data and counts objects passed should match.

A COMPASSContainer returns a list made up of the same components as input the model, but checks and sanitizes the supplied data to ensure that it conforms to the expectations outlied above.

set.seed(123)
n <- 10 ## number of samples
k <- 3 ## number of markers

## generate some sample data
sid_vec <- paste0("sid_", 1:n) ## sample ids; unique names used to denote samples
iid_vec <- rep_len( paste0("iid_", 1:(n/2) ), n ) ## individual ids

## generate n matrices of 'cell intensities'
data <- replicate(n, {
  nrow <- round(runif(1) * 1E2 + 1000)
  ncol <- k
  vals <- rexp( nrow * ncol, runif(1, 1E-5, 1E-3) )
  vals[ vals < 2000 ] <- 0
  output <- matrix(vals, nrow, ncol)
  output <- output[ apply(output, 1, sum) > 0, ]
  colnames(output) <- paste0("M", 1:k)
  return(output)
})
names(data) <- sid_vec

## make a sample metadata data.frame
meta <- data.frame(
  sid=sid_vec,
  iid=iid_vec,
  trt=rep( c("Control", "Treatment"), each=5 )
)

## generate an example total counts
## recall that cells not expressing any marker are not included
## in the 'data' matrices
counts <- sapply(data, nrow) + round( rnorm(n, 1E3, 1E2) )
counts <- setNames( as.integer(counts), names(counts) )

## insert everything into a COMPASSContainer
CC <- COMPASSContainer(data, counts, meta, "iid", "sid")