preprocess: Prepares Data for IDR Analysis
In idr2d: Irreproducible Discovery Rate for Genomic Interactions Data

Description Usage Arguments Value Examples

This method removes invalid values, establishes the correct ranking, and breaks ties prior to IDR analysis.

Inf and -Inf are replaced by max(x) * max_factor and min(x) / max_factor, respectively.

NA values in x are replaced by mean(x).

All values in x are transformed using the transformation specified in value_transformation.

Lastly, a small amount of noise is added to x to break ties. The magnitude of the noise is controlled by jitter_factor.

preprocess(
  x,
  value_transformation = c("identity", "additive_inverse", "multiplicative_inverse",
    "log", "log_additive_inverse"),
  max_factor = 1.5,
  jitter_factor = 1e-04
)

x

numeric vector of values

value_transformation

the values in x have to be transformed in a way such that when ordered in descending order, more significant interactions end up on top of the list. If the values in x are p-values, "log_additive_inverse" is recommended. The following transformations are supported:

`"identity"`	no transformation is performed on `x`
`"additive_inverse"`	`x. = -x`
`"multiplicative_inverse"`	`x. = 1 / x`
`"log"`	`x. = log(x)`. Note: zeros are replaced by `.Machine$double.xmin`
`"log_additive_inverse"`	`x. = -log(x)`, recommended if `x` are p-values. Note: zeros are replaced by `.Machine$double.xmin`

either "ascending" (more significant interactions have lower value in value column) or "descending" (more significant interactions have higher value in value column)

max_factor

numeric; controls the replacement values for Inf and -Inf. Inf are replaced by max(x) * max_factor and -Inf are replaced by min(x) / max_factor.

jitter_factor

numeric; controls the magnitude of the noise that is added to x. This is done to break ties in x. Set jitter_factor = NULL for no jitter.

numeric vector; transformed and stripped values of x, ready for IDR analysis