Anna E. Spiro

A scalable approach to investigating sequence-to-function predictions from personal genomes

This paper introduces SAGE-net, a framework for training sequence-to-function models using personal genomes, showing improved gene expression prediction but limited generalization, while DNA methylation shows better generalization.

A modality gap in personal-genome prediction by sequence-to-function models

The paper evaluates AlphaGenome's performance in predicting gene expression and chromatin accessibility from personal genomes, finding it excels in accessibility but struggles with gene expression.

Deep genomic models of allele-specific measurements

This paper introduces DeepAllele, a deep learning model for allele-specific gene regulation analysis, showing improved detection of cis-regulatory elements in F1 hybrid mice immune cells.

Benchmarking of deep neural networks for predicting personal gene expression from DNA sequence highlights shortcomings

This study benchmarks deep neural networks for predicting gene expression from DNA sequence across individuals and identifies limitations in predicting variant effects.

Principled Feature Attribution for Unsupervised Gene Expression Analysis

This paper introduces a novel unsupervised pathway attribution method that identifies major transcriptomic variation sources when combined with biologically-constrained models, applied to Alzheimer's disease brain samples.