olink_normalization_bridgeable: Identify if assays shared between Olink Explore 3072 and...

In OlinkAnalyze: Facilitate Analysis of Proteomic Data from Olink

Identify if assays shared between Olink Explore 3072 and Olink Explore HT can be bridged

Description

The function uses a dataset from Olink Explore 3072 and a dataset from Olink Explore HT, and examines if the matched assays between the two products can be normalized to each other. The input datasets should be exported from Olink software and should not be altered prior to importing them to this function.

Usage

olink_normalization_bridgeable(lst_df, ref_cols, seed = 1)

Arguments

lst_df	A named list of the 2 input datasets. First element should be the reference dataset from Olink Explore HT and the second element should originate from Olink Explore 3072.
ref_cols	A named list with the column names to use. Exported from olink_norm_input_check.
seed	Integer random seed (Default: seek = 1).

Details

All processes below assume that the first element from lst_df is the reference dataset (e.g. Olink Explore HT), and the other element of the list is the non-reference dataset (e.g. Olink Explore 3072). The input datasets have to be pre-processed by olink_norm_input_check which will take care of mapping of assay identifiers and various checks. Also, the input datasets should exclusively contain datapoints from bridge samples. When this function is called from the function olink_normalization, then the list is created seamlessly in the background, and the datasets have been already processed by olink_norm_input_check.

The input ref_cols is a named list masking column names of the reference dataset. This list is generated automatically from olink_norm_input_check when it is called from olink_normalization. In addition, olink_normalization has also utilized norm_internal_rename_cols to rename the columns of the non-reference dataset according to the ones of the reference dataset, hence all column names should match.

Value

A "tibble" in long format with the following columns:

• OlinkID: Underscore-separated Olink identifiers of matching assays between Olink Explore HT and Olink Explore 3072.

• BridgingRecommendation: A character vector indicating whether the matching assays are considered as bridgeable or not, and the recommended type of normalization to perform.

Author(s)

Amrita Kar Marianne Sandin Danai G. Topouza Klev Diamanti

Examples

# check input datasets
data_explore_check <- OlinkAnalyze:::olink_norm_input_check(
  df1 = OlinkAnalyze:::data_3k_small,
  df2 = OlinkAnalyze:::data_ht_small,
  overlapping_samples_df1 = intersect(
    x = unique(OlinkAnalyze:::data_3k_small$SampleID),
    y = unique(OlinkAnalyze:::data_ht_small$SampleID)
  ) |>
    (\(x) x[!grepl("CONTROL", x)])() |>
    head(20L),
  overlapping_samples_df2 = NULL,
  df1_project_nr = "P1",
  df2_project_nr = "P2",
  reference_project = "P2",
  reference_medians = NULL
)

# create lst_df
lst_df <- list(
  data_explore_check$ref_df,
  data_explore_check$not_ref_df
)
names(lst_df) <- c(data_explore_check$ref_name,
                   data_explore_check$not_ref_name)

# create ref_cols
ref_cols <- data_explore_check$ref_cols

# run olink_normalization_bridgeable
is_bridgeable_result <- OlinkAnalyze:::olink_normalization_bridgeable(
  lst_df = lst_df,
  ref_cols = ref_cols,
  seed = 1
)

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