The Cancer Data Science team and others at the Broad Institute came out with an article in Nature Communications today detailing a new method for normalizing and integrating multiple large RNAi screening datasets. It’s called DEMETER2, named after the Roman goddess of the harvest.
DEMETER2 uses a hierarchical Bayesian model to estimate gene dependency scores in cancer cells from measurements of multiple shRNAs. Like the original DEMETER, DEMETER2 accounts for the effects of “seed sequences” that align to multiple sites in the genome. Read more about it at the accompanying websiteWritten on November 2nd , 2018 by Jordan Bryan