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Introduction

• Olink R package: The Olink R package, known as Olink® Analyze, is designed to facilitate the analysis of proteomic data from Olink. It provides a versatile toolbox for handling Olink NPX data, including reading data, performing statistical tests, and generating QC plots.

• Installation: Olink® Analyze can be installed from CRAN using the command install.packages("OlinkAnalyze") or from GitHub using remotes::install_github(repo ='Olink-Proteomics/OlinkRPackage/OlinkAnalyze', ref = "main", build_vignettes = TRUE).

• Usage: The package includes functions for reading NPX data, generating QC plots, normalizing data, and performing statistical tests. Example functions include read_NPX, olink_dist_plot, olink_qc_plot, and olink_ttest.

• Applications: Olink's proteomics technology, based on Proximity Extension Assay (PEA), is used in various research areas including cardiovascular diseases, inflammation, oncology, and neurology.

• Training: There are training programs available for learning R language and its application in proteomics data analysis. These programs cover R language basics, programming, plotting, and statistical analysis.

Olink R Package [1]

• Description: The Olink R package, Olink® Analyze, is designed to facilitate the analysis of proteomic data from Olink.

• Functions: It includes functions for reading NPX data, performing statistical tests, and generating QC plots.

• Goal: The package aims to provide a versatile toolbox for handling Olink NPX data, making proteomic research more efficient.

• Availability: Olink® Analyze is available on CRAN and GitHub.

• Support: Users can report issues via email or GitHub.

Installation [1]

• CRAN: Install from CRAN using install.packages("OlinkAnalyze").

• GitHub: Install from GitHub using remotes::install_github(repo ='Olink-Proteomics/OlinkRPackage/OlinkAnalyze', ref = "main", build_vignettes = TRUE).

• Conda: Install into a new conda environment using conda create -n OlinkAnalyze -c conda-forge r-olinkanalyze.

• Vignettes: Access vignettes using browseVignettes("OlinkAnalyze").

• Support: Installation issues can be reported via email or GitHub.

Usage [1]

• Reading Data: Use read_NPX to read Olink NPX data from an Excel file.

• QC Plots: Generate QC plots using functions like olink_dist_plot and olink_qc_plot.

• Normalization: Normalize data using functions like olink_normalization.

• Statistical Tests: Perform statistical tests using functions like olink_ttest.

• Visualization: Visualize results using functions like olink_volcano_plot.

Applications [2]

• Cardiovascular Diseases: Olink's proteomics technology is used to study cardiovascular diseases.

• Inflammation: The technology is also applied in inflammation research.

• Oncology: Olink panels are used in cancer research.

• Neurology: The technology is used to study neurological diseases.

• Biomarker Discovery: Olink's technology helps in discovering biomarkers for various diseases.

Training Programs [3]

• R Language Basics: Training programs cover the basics of R language.

• Programming: Courses include R language programming.

• Plotting: Training includes R language plotting techniques.

• Statistical Analysis: Programs cover statistical analysis using R.

• Bioinformatics: Courses include bioinformatics analysis using R.

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