How to capture activity of thousands of genes in a single cell? It’s MAGIC

The Markov Affinity-based Graph Imputation of Cells is able to reveal interactions between thousands of genes in a single cell, and how those change over time.
Side by side graphs depicting data before and after researchers used Markov Affinity-based Graph Imputation of Cells

A new method that can capture the global range of gene activity within single cells is literally MAGIC.

The Markov Affinity-based Graph Imputation of Cells enables researchers to recapture much of the data missed by current technologies that measure the RNA of thousands of genes within a cell at a given moment. In the process, it is also able to reveal interactions between these genes and how those change over time. The algorithm infers the transcriptome across multiple dimensions to give scientists a more robust view of activity within cells.

We can measure 20,000 genes at once and restore multidimensional relationships between them,” said Yale’s Smita Krishnaswamy of the Departments of Genetics and Computer Science and co-senior author of the paper.

The work by Yale scientists Smita Krishnaswamy, David van Dijk, Guy Wolf, and Kevin Moon, and their colleagues at Sloan-Kettering Institute was published June 28 in the journal Cell.

Share this with Facebook Share this with X Share this with LinkedIn Share this with Email Print this

Media Contact

Bill Hathaway: william.hathaway@yale.edu, 203-432-1322