About

This analytical tool was developed to streamline the processing of serological data generated using a validated high-throughput multiplex serological assay for measuring antibodies to Plasmodium vivax (Longley et al 2020). This tool also aims to make the downstream processing, quality control, and interpretation of the raw data generated from this serological assay accessible to all researchers without the need for a specialist background in statistical methods and advanced programming.

Acknowledgements

The code and scripts used to develop this R Shiny web application are available on GitHub. The scripts and functions used in this application were developed by Lauren Smith and Dionne Argyropoulos, with contributions from the following researchers:

  • Dionne Argyropoulos, WEHI (App development)
  • Lauren Smith, WEHI (classification algorithm development)
  • Connie Li Wai Suen, WEHI (original 5-parameter logistic model development for conversion of MFI to RAU for PNG Pool Standard Curve)
  • Eamon Conway for ongoing advice, WEHI (5-parameter logistic model development for conversion of MFI to RAU for Ethiopian Pool Standard Curve)
  • Thomas Obadia, Institut Pasteur (development of serological classification algorithm, application scripts and functions for P. vivax)
  • Shazia Ruybal-Pesántez, WEHI* (application scripts and functions for SARS-Cov-2)
  • Narimane Nekkab** and Michael White, Institut Pasteur (original development of serological classification algorithm for P. vivax)

Current address: *Imperial College London; **Swiss Tropical and Public Health Institute.

Many thanks to Pailene Lim, Anju Abraham, Macie Lamont, Caitlin Bourke and Nick Walker for trailing and providing feedback on this tool.

This work was conducted under supervision of Rhea Longley and Ivo Mueller.

Funding

We acknowledge grant funding from the Bill and Melinda Gates Foundation (INV-051542), the WEHI Global Impact Fund, and a Ramaciotti Health Investment Grant (2022HIG52), to support development of this RShiny App.