When a cell falls ill, the activity of thousands of genes inside it changes. Scientists want to know which gene set those changes in motion. RevPert works like a detective with a database of fingerprints: it compares the cell's state against a catalog of genes that researchers already know how to switch off in the lab, and it finds the closest matches.
The old approach was simply to look at which genes changed the most and treat them as suspects. But that doesn't always work: the real culprit may change only slightly, while a noisy gene changes a lot. RevPert instead compares the entire shift against knockout fingerprints. What's more, it accounts for direction: if knocking out a gene usually pushes the cell one way and the disease pulls it the other way, that gene gets a low score.
The method was tested on cells with known knockouts: RevPert put the right gene at the top of the list more often than older approaches did. It was then applied to drug-resistant cancer cells, and it found genes that had previously slipped past researchers' attention. Now biologists can test these genes in experiments without sifting through thousands of candidates.
Think of how a detective tracks down a culprit from fingerprints: RevPert does the same, but instead of fingers it uses the expression profiles of thousands of genes. And it doesn't just look for a match; it accounts for the direction of the shift, as if the detective could tell who left a print and who wiped it away.
Not published on arXiv. Here are its page, the PDF and the formalization: you can check it yourself, not only read our account.