Single-cell genomic technologies provide an unprecedented opportunity to define molecular cell types in a data-driven fashion, but present unique data integration challenges. Here we present UINMF, a computational tool designed to improve dataset integrations by leveraging unshared features.

The objective of our research program is to better understand and improve nitrogen (N) use efficiency in maize. One of these strategies was to study the impacts of environmental conditions, and allelic variation of the cytosolic glutamine synthetase enzyme on maize hybrid kernel production.