Characterizing tissue composition at the cellular level is essential for understanding the human body in health and disease, and has been one of the frontiers in biology for centuries. Recently developed single-cell RNA-sequencing (scRNA-seq) techniques now allow obtaining global molecular snapshots of single cells, which has proven to be a powerful tool to explore biology on the cellular level. By employing uncontrolled cell capture and random barcoding, droplet-based platforms are capable of rapidly processing thousands of cells at low per cell costs. However, this strategy has limited their applicability in other, more specialized, experimental scenarios, for instance the processing of small samples (< 500 cells) or the integration of cell sorting and imaging. This work aimed to develop deterministic control layers for the cell encapsulation process and the cell barcoding process, to further the capacities of these powerful systems and to enable the integration of the aforementioned functionalities. Initially, in Chapter 2 we re-engineered "Drop-seq", a commonly used droplet-based scRNA-seq approach, to render it compatible with air pressure control systems, and to maximize protocol efficiencies for the library generation process. In Chapter 3, based on these adaptions, we developed a control layer comprised of a microfluidic chip containing microvalves, which performed particularly well on low input cell numbers (~ 100 cells). We utilized DisCo to profile the heterogeneity of individual intestinal organoids, an outstanding problem in the field. Using this data we identified two previously described distinct organoid subtypes, and a so far unknown subtype, enriched in immature and mature goblet cells, which we name "gobloid". Our results demonstrated that the utilization of scRNA-seq for small individual tissues is a powerful approach to explore heterogeneity. In Chapter 4 we developed a droplet-based approach to barcode cells with predetermined barcodes. The use of defined barcodes would allow processing multiple samples in the same run, and ultimately enable the collection of phenotypic information during encapsulation, for instance by imaging. Furthermore, we aimed to utilize liquid reagents, injected into droplets, to maximize the flexibility of our system. On this system we developed a novel dual-layer barcoding chemistry, to achieve substantial throughput of ~1000 cells per run. We compared the sensitivity of this approach to DisCo and observed that even in this early stage of development it outperformed the latter. Finally, we demonstrated that using this platform it is now possible to arbitrarily multiplex samples, which was not possible before without using additional cell labeling strategies. The final product of this work is a flexible platform technology for scRNA-seq experimentation with advanced needs. Our technology offers new perspectives for the integration of routine imaging in the scRNA-seq workflow or unifying functions on one platform by e.g. the integration of sorting. We believe these functionalities substantially increase the power of droplet-based scRNA-seq, and will open new experimental opportunities: Our approach could be transformative for efficient profiling of rare tissues or diagnostic samples, and systematic study of the relationship between the morphology and molecular state of a cell.