Cheng Luo

When a target cell line has no drug measurements, GRAFT links that line's genetic perturbation responses to drug responses measured in source cells and predicts the transcriptional changes a drug would induce. In leave-one-line-out evaluation across five LINCS cancer lines, GRAFT-D0 reached a mean Top20 Pearson correlation of 0.734, above the source mean of 0.493 and the strongest comparator PRnet at 0.689; across five external cellular contexts the equally weighted mean Top20 correlation was 0.606 against a source mean of 0.416. The method rests on a conditioning state built from how the target's genetic responses differ from source references, and predictions still improve when target genetic measurements are few, though gains vary with data quality and source coverage.

When a target cell line has no drug measurements, GRAFT links that line's genetic perturbation responses to drug responses measured in source cells and predicts the transcriptional changes a drug would induce. In leave-one-line-out evaluation across five LINCS cancer lines, GRAFT-D0 reached a mean Top20 Pearson correlation of 0.734, above the source mean of 0.493 and the strongest comparator PRnet at 0.689; across five external cellular contexts the equally weighted mean Top20 correlation was 0.606 against a source mean of 0.416. The method rests on a conditioning state built from how the target's genetic responses differ from source references, and predictions still improve when target genetic measurements are few, though gains vary with data quality and source coverage.