Bio: April Kriebel received her Ph.D. in the Department of Computational Medicine and Bioinformatics. She joined Dr. Joshua Welch’s laboratory in 2020, and her dissertation work was focused on developing computational methods for integrating molecular and anatomical data with spatial transcriptomics. She is an alumna of the Genome Science Training Program and an F-31 recipient.

Her first project as a graduate student focused on the development of UINMF, a single-cell dataset integration algorithm that could integrate datasets using both shared and unshared features. This algorithm proved especially advantageous when integrating scRNA-seq datasets with spatial transcriptomic datasets that often measured fewer genes. Genes not captured during the spatial transcriptomic protocol but were measured in the scRNA-seq data could now be leveraged when integrating the two datasets, leading to the identification of more refined cell type distinctions within the spatial transcriptomics data.
Her subsequent efforts were part of the Welch Lab’s contributions to the BRAIN consortium. The project aimed to construct a whole-brain mouse atlas with spatial resolution. The resulting atlas encompasses over 10 million single-cell profiles from 18 regions across the mouse brain. Two spatial transcriptomic datasets – the Allen Institute’s in situ hybridization dataset and the whole-brain Slide-seq dataset – were deconvolved to define spatial distributions for the identified cell type profiles. Identifying the spatial distributions of the molecular cell types allowed correlations to be drawn between molecular cell types and anatomical features and physiological responses within the brain.
April is particularly excited about disseminating their results, as they are constructing an interactive portal that will allow users to examine the spatial distribution of molecular cell types in conjunction with anatomical and physiological features, such as neuronal projection data, vascular density, and c-Fos response after foot shock.