Agenda

In this thesis, I present the development of user-friendly and web-based tools for several types of transcriptomics data. First, I developed a R-shiny app to analyze bulk RNA-seq data, RNfuzzyApp. It offers several tools for classical bulk differential expression analysis. Moreover, RNfuzzyApp is the so far only app that helps users perform time-series analysis with the fuzzy clustering algorithm Mfuzz, by partially automating the process for fuzzy clustering analysis. Secondly, I developed an update of the mitoXplorer 2.0 platform for mitochondria-centric data analysis of RNA sequencing data. With this update to mitoXplorer 3.0, the platform is now able to integrate sc-RNA-sequencing data. For data pre-processing, I developed an automated script that first generates pseudo-bulk data and performs pseudo-bulk based differential expression analysis based on annotated cell types. Secondly, the script extracts the mito-genes from the single-cell count matrix, creating a mito-gene specific scRNA-seq dataset for direct upload and data mining in the mitoXplorer 3.0 platform, with novel interactive interfaces that I have developed. Finally, I extend the development of mitoXplorer 3.0 to the development of its first sister platform, ataxiaXplorer, to explore and analyze bulk- and single-cell transcriptomics data in the context of cerebellar ataxias.