olink_norm_input_class: Check classes of input in olink_normalization function

In OlinkAnalyze: Facilitate Analysis of Proteomic Data from Olink

Check classes of input in olink_normalization function

Description

Check if df1, df2 and/or reference_medians are tibble or ArrowDataset datasets; if overlapping_samples_df1 and/or overlapping_samples_df2 are character vectors; and if df1_project_nr, df2_project_nr and/or reference_project are scalar character vectors.

Usage

olink_norm_input_class(
  df1,
  df2,
  overlapping_samples_df1,
  overlapping_samples_df2,
  df1_project_nr,
  df2_project_nr,
  reference_project,
  reference_medians,
  norm_mode
)

Arguments

df1	First dataset to be used in normalization (required).
df2	Second dataset to be used in normalization.
overlapping_samples_df1	Samples to be used for adjustment factor calculation in df1 (required).
overlapping_samples_df2	Samples to be used for adjustment factor calculation in df2.
df1_project_nr	Project name of first dataset (df1).
df2_project_nr	Project name of first dataset (df2).
reference_project	Project name of reference_project. Should be one of df1_project_nr or df2_project_nr. Indicates the project to which the other project is adjusted to.
reference_medians	Dataset with columns "OlinkID" and "Reference_NPX". Used for reference median normalization.
norm_mode	Scalar character from olink_norm_modes with the normalization to be performed. Output from olink_norm_input_validate.

Value

NULL unless there is an error

Author(s)

Klev Diamanti

OlinkAnalyze documentation built on Sept. 25, 2024, 9:07 a.m.