High false sign rates in transcriptome-wide association studies
P. Gerlach; Nikhil Milind; Jeffrey P. Spence; Jonathan K. Pritchard · 2026 · Nature Genetics
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
Abstract Transcriptome-wide association studies (TWAS) are widely used to identify genes involved in complex traits and to infer the direction of gene effects on traits. However, despite their popularity, it remains unclear how accurately TWAS recover the true direction of a gene’s effect on a trait. Here we estimate the false sign rate of TWAS for plasma proteins, leveraging the expectation that increased gene expression should generally increase protein expression. We then extend this framework to complex traits, where loss-of-function burden tests provide the expected direction of effect. I
Abstract by P. Gerlach; Nikhil Milind; Jeffrey P. Spence; Jonathan K. Pritchard, Nature Genetics (2026) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.1038/s41588-026-02796-4