R is well-known for its unsurpassed provision of well documented statistical functions and packages in the default installation. Less well-known is its excellent support for spatial data through packages such as sf, terra, and stars. A thriving ecosystem of diverse and often topic-specific packages build on these foundations, making R a powerful command-line GIS (Geographic Information System) for reproducible research. However, dedicated GIS software (e.g. QGIS) offers specific processing algorithms that are either not available in R, or may achieve a higher level of performance than their equivalents in R. This presentation describes how it is now possible to combine the strengths of R and QGIS through R packages that interface processing algorithms provided by QGIS. These packages (qgisprocess, qgis) allow users to create data processing pipelines that combine R and QGIS algorithms almost seamlessly. This talk discusses the current state of these R packages and demonstrate the usage of their most important functions by example. Finally, it sheds light on future development directions and seek feedback from the community.