In silico variant interpretation pipelines are an integral part in research and genome diagnostics. However, challenges still remain for automated variant interpretation and candidate shortlisting. For instance, reliability is affected by variability in input data caused by different sequencing platforms, erroneous nomenclature and changing experimental conditions. Similarly, differences in predictive algorithms could result in discordant results and scalability is essential to accommodate large amounts of input data, such as Whole Genome Sequencing (WGS). To accelerate causal variant detection and innovation in genome diagnostics and research, we developed the MOLGENIS Variant Interpretation Pipeline (VIP). VIP is a flexible and open-source computational pipeline to generate interactive reports of variants in Whole Exome Sequencing (WES) and WGS data for expert interpretation. VIP is applicable to short- and long-read data from different platforms and offers tools for increased sensitivity. For this purpose, a configurable decision tree, filters based on Human Phenotype Ontology (HPO) and gene inheritance can be used to pinpoint disease-causing variants or to finetune a query for specific variants. Additionally, we present a step-by-step protocol describing how to use VIP to annotate, classify and filter genetic variants of patients with a rare disease that has a suspected genetic cause. Finally, we demonstrate how VIP performs using 25,664 previously classified variants from the Data Sharing initiative of the Vereniging van Klinisch Genetische Laboratoriumdiagnostiek (VKGL), a cohort of 18 patients from routine diagnostics and a cohort of 41 patients with a rare diseases (RD) that were not diagnosed in routine diagnostics but were solved within the EU wide project to solve rare diseases (EU-Solve-RD) using novel omics approaches. The protocol requires bioinformatic knowledge to configure and afterwards every diagnostic professional is able to perform an analysis within 5 hours.