Calculate score for each feature in each cell

cal_score_init(
  expr,
  tf = c("logtf", "tf"),
  idf = "prob",
  iae = "prob",
  par.idf = NULL,
  par.iae = NULL,
  return.intermediate = FALSE
)

Arguments

expr: a count matrix, features in row and cells in column
tf: a character, specify the TF method to use, can be "tf" or "logtf"
idf: a character, specify the IDF method to use. Available methods can be accessed using idf_iae_methods()
iae: a character, specify the IAE method to use. Available methods can be accessed using idf_iae_methods()
par.idf: other parameters for specified IDF methods
par.iae: other parameters for specified IAE methods
return.intermediate: logical, if TRUE the returned list also contains the intermediate tf, idf and iae objects. Default FALSE keeps only the combined score to avoid the memory overhead of three extra feature-by-cell matrices on large inputs.

Value

a list always containing score; when return.intermediate = TRUE the list additionally contains tf, idf and iae.

Examples

data <- matrix(rpois(100, 2), 10, dimnames = list(1:10))
label <- sample(c("A", "B"), 10, replace = TRUE)
smartid:::cal_score_init(data,
  par.idf = list(label = label),
  par.iae = list(label = label)
)
#> $score
#>    [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#> 1     0    0    0    0    0    0    0    0    0     0
#> 2     0    0    0    0    0    0    0    0    0     0
#> 3     0    0    0    0    0    0    0    0    0     0
#> 4     0    0    0    0    0    0    0    0    0     0
#> 5     0    0    0    0    0    0    0    0    0     0
#> 6     0    0    0    0    0    0    0    0    0     0
#> 7     0    0    0    0    0    0    0    0    0     0
#> 8     0    0    0    0    0    0    0    0    0     0
#> 9     0    0    0    0    0    0    0    0    0     0
#> 10    0    0    0    0    0    0    0    0    0     0
#>