Genomics is a highly dynamic field with continuous improvement of existing single cell technologies. In recent years we experienced a rapid growth of both the experimental and computational methods, allowing us to further our understanding of tissue heterogeneity and biological processes assessed for thousands of cells at the same time. The existing methods however are characterized by a number of limitations: high cost, limited throughput and technical variability, which are often prohibiting the study of complex tissues at sufficient depth or while processing multiple samples in parallel. To overcome these limitations and alleviate the high cost of high throughput genomics assays, we are developing and optimizing methods for enhancing single nucleus droplet overloading. These methods combine two main advances in single cell genomics technologies: combinatorial indexing and in-droplet barcoding. They depend on an addition of a pre-indexing step prior to droplet generation using the 10X Genomics assays, allowing then to massively overload the system and resulting in many droplets containing multiple nuclei. The pre-indexing step is carried out in a multi-well plate and labels all fragments within nuclei with a unique, well-specific barcode. This allows processing of multiple samples at the same time as well as increasing the number of nuclei recovered per sample, thus reducing the cost and decreasing the technical variability. The nuclei are then pooled and packaged in droplets with a barcoding mix and beads carrying uniquely barcoded primers, where the second index is added. We can then resolve single nuclei by a unique combination of two indices. These overloading methods however are associated with their own pitfalls: index hopping and fragment leaking, leading to erroneous assignment of fragments to nuclei they did not originate from. In our work, we have optimized the conditions of pre-indexing and droplet barcoding steps to enhance confidence of per-nucleus fragment assignment.