Changes in version 0.99.0                        

New features

All new features allow for tidy selection. Making it easier to evaluate
different types of data for the same method. For instance, you can
specify the columns to use as strings, integer position, symbol or
expression.

Methods

  - New decouple() integrates the various member functions of the
    decoupleR statistics for centralized evaluation.

  - New family decoupleR statists for shared documentation is made up
    of:
    
      - New run_gsva() incorporate a convinient wrapper for
        GSVA::gsva().
      - New run_mean() calculates both the unnormalized regulatory
        activity and the normalized (i.e. z-score) one based on an
        empirical distribution.
      - New run_ora() fisher exact test to calculate the regulatory
        activity.
      - New run_pscira() uses a logic equivalent to run_mean() with the
        difference that it does not accept a column of likelihood.
      - New run_scira() calculates the regulatory activity through the
        coefficient $\beta_1$ of an adjusted linear model.
      - New run_viper() incorporate a convinient wrapper for
        viper::viper().

Converters

  - New functions family convert_to_ variants that allows the conversion
    of data to a standard format.
      - New convert_to_() return the entry without modification.
      - New convert_to_gsva() return a list of regulons suitable for
        GSVA::gsva().
      - New convert_to_mean() return a tibble with four columns: tf,
        target, mor and likelihood.
      - New convert_to_ora() returns a named list of regulons; tf with
        associated targets.
      - New convert_to_pscira() returns a tibble with three columns: tf,
        target and mor.
      - New convert_to_scira() returns a tibble with three columns: tf,
        target and mor.
      - New convert_to_viper() return a list of regulons suitable for
        viper::viper()