scRNAseq_KNIME workflow: A Customizable, Locally Executable, Interactive and Automated KNIME workflow for single-cell RNA seq

Abstract

AbstractSummarySingle-cell RNA sequencing (scRNA-seq) is nowadays widely used to measure gene expression in individual cells, but meaningful biological interpretation of the generated scRNA-seq data remains a complicated task. Indeed, expertise in both the biological domain under study, statistics, and computer programming are prerequisite for thorough analysis of scRNA-seq data. However, biological experts may lack data science expertise, and bioinformatician’s limited understanding of the biology may lead to time-consuming iterations.A user-friendly and automated workflow with possibility for customization is hence of a wide interest for both the biological and bioinformatics communities, and for their fruitful collaborations. Here, we propose a locally installable, user-friendly, interactive, and automated workflow that allows the users to perform the main steps of scRNA-seq data analysis. The interface is composed of graphical entities dedicated to specific and modifiable tasks. It can easily be used by biologists and can also serve as a customizable basis for bioinformaticians.Availability and implementationThe workflow is developed in KNIME; its tasks were defined by R scripts using KNIME R nodes. The workflow is publicly available athttps://github.com/Saminakausar/scRNAseq_KNIME.Contact:anais.baudot@univ-amu.fr;muhasif123@gmail.com