SUMMARY: Many factors can influence results in clinical research, in particular bias in the distribution of samples prior to biochemical preparation. Well Plate Maker is a user-friendly application to design single- or multiple-well plate assays. It allows multiple group experiments to be randomized and therefore helps to reduce possible batch effects. Although primarily fathered to optimize the design of clinical sample analysis by high throughput mass spectrometry (e.g. proteomics or metabolomics), it includes multiple options to limit edge-of-plate effects, to incorporate control samples, or to limit cross-contamination. It thus fits the constraints of many experimental fields. AVAILABILITY AND IMPLEMENTATION: Well Plate Maker is implemented in R and available at Bioconductor repository (https://bioconductor.org/packages/wpm) under the open source Artistic 2.0 license. In addition to classical scripting, it can be used through a graphical user interface, developed with Shiny technology. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
SUMMARY: Many factors can influence results in clinical research, in particular bias in the distribution of samples prior to biochemical preparation. Well Plate Maker is a user-friendly application to design single- or multiple-well plate assays. It allows multiple group experiments to be randomized and therefore helps to reduce possible batch effects. Although primarily fathered to optimize the design of clinical sample analysis by high throughput mass spectrometry (e.g. proteomics or metabolomics), it includes multiple options to limit edge-of-plate effects, to incorporate control samples, or to limit cross-contamination. It thus fits the constraints of many experimental fields. AVAILABILITY AND IMPLEMENTATION: Well Plate Maker is implemented in R and available at Bioconductor repository (https://bioconductor.org/packages/wpm) under the open source Artistic 2.0 license. In addition to classical scripting, it can be used through a graphical user interface, developed with Shiny technology. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Authors: Eric W Deutsch; Gilbert S Omenn; Zhi Sun; Michal Maes; Maria Pernemalm; Krishnan K Palaniappan; Natasha Letunica; Yves Vandenbrouck; Virginie Brun; Sheng-Ce Tao; Xiaobo Yu; Philipp E Geyer; Vera Ignjatovic; Robert L Moritz; Jochen M Schwenk Journal: J Proteome Res Date: 2021-10-21 Impact factor: 5.370
Authors: Steffi De Meyer; Jeroen Vanbrabant; Jolien M Schaeverbeke; Mariska Reinartz; Emma S Luckett; Patrick Dupont; Koen Van Laere; Erik Stoops; Eugeen Vanmechelen; Koen Poesen; Rik Vandenberghe Journal: Ann Clin Transl Neurol Date: 2022-05-03 Impact factor: 5.430