Excited to share a new preprint from my & @Pejminister labs: Quantifying genetic regulatory variation in human populations improves transcriptome analysis in rare disease patients biorxiv.org/content/10.110…
We developed a new method, Analysis of Expression VAriation (ANEVA) to model allelic expression data to quantify population genetic regulatory variation for each gene. This was applied in multi-tissue #GTEx data...
Genes with low amount of genetic regulatory variation are enriched for coding constraint and rare disease genes - building a link between intolerance for dosage variation regardless of variation type.
Our ANEVA Dosage Outlier Test then uses allelic expression data from any individual and the population reference variation to find the genes where the individual seems to carry a variant with an unusually strong effect on gene expression.
Applying ANEVA-DOT to muscle disease patients (from @beryl_bbc , @dgmacarthur et al.) showed really good specificity and sensitivity in previously diagnosed patients, and indicated new diagnoses that has been missed in previous WES, WGS and RNA-seq analyses.
The advantage here is that allelic expression is powerful in capturing _genetic_ regulatory effects, allowing comparison of patients samples to pop reference like GTEx - a bit like prioritizing WES with coding constraint scores. Ofc, the reference stats & software are available.
This paper is a result of absolutely brilliant work by @Pejminister, first in my lab and then in his own. Many others contributed a lot - special thanks to @stephanecastel, @beryl_bbc and @dgmacarthur.
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