The increasing number of single-cell and bulk RNAseq datasets describing complex gene expression profiles across various organisms necessitates an intuitive tool for rapid comparative analysis. Introducing SPOT, a powerful web tool designed for differential expression analysis and fast ranking of genes that fit specific transcription profiles of interest. Utilizing a heuristic approach, the SPOT algorithm ranks genes based on their proximity to the user-defined gene expression profile. The top results are visualized as a table, bar chart, or dot plot and can be exported as an Excel file. While generally applicable, SPOT has been tested on RNAseq data from malaria parasites undergoing multiple stage transformations, data from various human organs during development, and cell lines infected by the SARS-CoV-2 virus. SPOT enables non-bioinformaticians to easily analyze their own datasets. Reference: Elias Farr et al. SPOT: a web-tool enabling Swift Profiling Of Transcriptomes

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