2020/11/25 by Joachim Goedhart, Martijn S. Luijsterburg · 8 citations
Chemistry · Biochemistry, Genetics and Molecular Biology · #Advanced Proteomics Techniques and Applications #Metabolomics and Mass Spectrometry Studies #Bioinformatics and Genomic Networks
paper · pdf · doi:10.1038/s41598-020-76603-3
openalex publication_date 2020/11/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/25
Comparative genome- and proteome-wide screens yield large amounts of data. To efficiently present such datasets and to simplify the identification of hits, the results are often presented in a type of scatterplot known as a volcano plot, which shows a measure of effect size versus a measure of significance. The data points with the largest effect size and a statistical significance beyond a user-defined threshold are considered as hits. Such hits are usually annotated in the plot by a label with their name. Volcano plots can represent ten thousands of data points, of which typically only a handful is annotated. The information of data that is not annotated is hardly or not accessible. To simplify access to the data and enable its re-use, we have developed an open source and online web tool with R/Shiny. The web app is named VolcaNoseR and it can be used to create, explore, label and share volcano plots ( https://huygens.science.uva.nl/VolcaNoseR ). When the data is stored in an online data repository, the web app can retrieve that data together with user-defined settings to generate a customized, interactive volcano plot. Users can interact with the data, adjust the plot and share their modified plot together with the underlying data. Therefore, VolcaNoseR increases the transparency and re-use of large comparative genome- and proteome-wide datasets.