St. Jude scientists create scalable solution for analyzing single-cell data
Researchers have amassed vast single-cell gene expression databases to understand how the smallest details impact human biology. However, current analysis methods struggle with the large volume of data and, as a result, produce biased and contradictory findings. Scientists at St. Jude Children’s Research Hospital created a machine-learning algorithm capable of scaling with these single-cell data repositories to deliver more accurate results. The new method was published today in Cell Genomics.
Before single-cell analysis, bulk gene expression data ...









