Wrapper function to generate blitzGSEA parameters

Wrapper function to generate blitzGSEA parameters

Usage

params_blitzgsea(
  min_size = 5L,
  max_size = 500L,
  permutations = 2000L,
  anchors = 40L,
  symmetric = FALSE,
  centre = TRUE,
  ks_test = TRUE,
  seed = 42
)

Arguments

min_size

Integer. Minimum number of genes per gene set. Defaults to 5L.

max_size

Integer. Maximum number of genes per gene set. Defaults to 500L.

permutations

Integer. Random gene sets drawn per anchor size during calibration. Below 1000L the two tails are pooled into a single gamma regardless of symmetric. Defaults to 2000L.

anchors

Integer. Number of log-spaced anchor sizes requested. Sizes that collide after rounding are collapsed, so the realised grid is usually a little smaller. Defaults to 40L.

symmetric

Boolean. Pool both tails into one gamma instead of fitting them separately. Defaults to FALSE.

centre

Boolean. Centre the signature on its mean before scoring. The enrichment score is not invariant to an offset, so the calibration and the scoring have to agree on this. Defaults to TRUE.

ks_test

Boolean. Run the Kolmogorov-Smirnov goodness-of-fit diagnostic at every anchor. Costs a sort per anchor. Defaults to TRUE.

seed

Numeric. Random seed for the calibration. Defaults to 42.0.

Value

A named list with the following elements:

• min_size - Integer. Minimum number of genes per gene set. Defaults to 5L.

• max_size - Integer. Maximum number of genes per gene set. Defaults to 500L.

• permutations - Integer. Random gene sets drawn per anchor size during calibration. Below 1000L the two tails are pooled into a single gamma regardless of symmetric. Defaults to 2000L.

• anchors - Integer. Number of log-spaced anchor sizes requested. Sizes that collide after rounding are collapsed, so the realised grid is usually a little smaller. Defaults to 40L.

• symmetric - Boolean. Pool both tails into one gamma instead of fitting them separately. Defaults to FALSE.

• centre - Boolean. Centre the signature on its mean before scoring. The enrichment score is not invariant to an offset, so the calibration and the scoring have to agree on this. Defaults to TRUE.

• ks_test - Boolean. Run the Kolmogorov-Smirnov goodness-of-fit diagnostic at every anchor. Costs a sort per anchor. Defaults to TRUE.

• seed - Numeric. Random seed for the calibration. Defaults to 42.0.

References

Lachmann, et al., Bioinformatics, 2022