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Generate sample weight matrix from TMB values

Source: R/selectX_create.r
generateW_mean_tmb.Rd

Computes a per-sample weight matrix based on the ratio of each sample's TMB to the expected (mean) TMB. Samples with higher-than-expected TMB receive lower weights via a penalty lambda, controlled by the fold-change threshold tau.

Usage

generateW_mean_tmb(
  tmb,
  mean_tmb,
  ngenes,
  lambda = 0.3,
  tau = 1,
  discrete = TRUE
)

Arguments

tmb

Numeric vector of per-sample TMB values.

mean_tmb

Numeric scalar; the reference (expected) TMB used to compute fold changes.

ngenes

Integer; number of genes (rows) in the output weight matrix.

lambda

Numeric; weight penalty factor. Higher values penalise high-TMB samples more strongly (default 0.3).

tau

Numeric; fold-change threshold below which no penalty is applied (default 1).

discrete

Logical; if TRUE, fold changes are rounded up before applying the penalty (default TRUE).

Value

Numeric matrix of sample weights (ngenes x length(tmb)).

Examples

tmb      <- c(s1 = 10, s2 = 50, s3 = 20)
mean_tmb <- 25
generateW_mean_tmb(tmb, mean_tmb, ngenes = 3)
#>      [,1]      [,2] [,3]
#> [1,]    1 0.7692308    1
#> [2,]    1 0.7692308    1
#> [3,]    1 0.7692308    1