The Salomonis lab is working to understand the role of alternative splicing in human development and disease and integrate these results with epigenetic, gene expression, proteomic and single-cell sequencing data. They also develop new computational methods for analyzing data generated by emerging sequencing technologies.  

The lab’s primary goal is to uncover the origins of human disease through the integration of genetic, molecular and cellular data. To achieve this goal, they build “unsupervised” techniques to extract hidden sources of molecular variation from patient and single-cell genomics datasets as well as accurately quantify the underlying measurements.

The Salomonis team also develops easy-to-use software environments that are accessible to non-computational scientists including new software and algorithms to identify complex functional relationships from whole transcriptome data. Open source computational tools they have developed to understand the impact of gene expression changes on biological pathways include GenMAPP, GO-Elite, and AltAnalyze, an easy-to-use application for the end-to-end analysis of single-cell and bulk RNA-Seq data. These applications have been used in hundreds of studies in laboratories throughout the world.

Join the Lab

The Salomonis lab is recruiting lab members for postdoctoral, graduate and undergraduate positions. Learn more about joining our team.