Comparing large, complex, and high-dimensional datasets can be difficult since the bioinformatics tools needed are lacking. This is particularly important in the study of disease, which requires comparing patient samples to healthy control subjects.

Eliezyer Fermino de Oliveira, Lucas Sjulson, M.D., Ph.D., and colleagues have now developed an open-source tool to analyze and compare large datasets. In findings published online on February 7 in PLOS Computational Biology, the authors show that their tool can successfully analyze complex biological datasets including single-cell RNA sequencing and neurophysiological brain recordings. The tool should be especially useful for discovering previously obscure biomarkers.

Dr. Sjulson is an assistant professor of psychiatry and behavioral sciences and in the Dominick P. Purpura Department of Neuroscience at Einstein. Mr. Fermino de Oliveira is a graduate student in Dr. Sjulson's lab.