HORNET: tools to find genes with causal evidence and their regulatory networks using eQTLs
Noah Lorincz-Comi; Yihe Yang; Jayakrishnan Ajayakumar; Makaela Mews; Valentina Bermudez; William Bush; Xiaofeng Zhu · 2024 · Bioinformatics Advances
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 (excerpt)
Abstract Motivation Nearly two decades of genome-wide association studies (GWAS) have identify thousands of disease-associated genetic variants, but very few genes with evidence of causality. Recent methodological advances demonstrate that…
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Metadata source: Crossref · DOI 10.1093/bioadv/vbaf068