Automated quantitative trait locus analysis (AutoQTL).

Philip J FredaAttri GhoshElizabeth ZhangTianhao LuoApurva ChitreOksana PolesskayaCeline L St PierreJianjun GaoConnor D MartinHao ChenAngel G Garcia-MartinezTengfei WangWenyan HanKeita IshiwariPaul MeyerAlexander LamparelliChristopher P KingAbraham A PalmerRuowang LiJason H Moore

Published in: bioRxiv : the preprint server for biology (2023)

This proof-of-concept illustrates that automated machine learning techniques can be applied to genetic data and has the potential to detect both additive and non-additive effects via various optimal solutions and feature importance metrics. In the future, we aim to expand AutoQTL to accommodate omics-level datasets with intelligent feature selection strategies.

Keyphrases

machine learning
deep learning
big data
artificial intelligence
genome wide
single cell
electronic health record
rna seq
high resolution
current status
risk assessment
gene expression
data analysis
climate change