Orchestrating multi-state QTL analysis with Bioconductor

The scope of many Quantitative Trait Locus (QTL) mapping studies has increased to include different cellular and environmental states. However, drawing biologically relevant conclusions from the large, high-dimensional data that come from multi-state QTL mapping studies is not straightforward.

To address this problem, we introduce two R packages, QTLExperiment and multistateQTL. The QTLExperiment package provides a robust container for storing and manipulating QTL summary statistics and associated metadata. Building upon existing Bioconductor infrastructure and conventions, this object class is consistent, user-friendly, and well-documented. The multistateQTL package introduces tools to facilitate the analysis of multi-state QTL data stored in a QTLExperiment container. This package provides methods for statistical analysis, quantification of sharing, classification of multi-state QTL associations, visualization of the data, and more. It also provides flexible methods for simulating multi-state QTL summary statistics with user-defined properties. The packages QTLExperiment and multistateQTL are open-source and are freely available on Bioconductor ( https://www.bioconductor.org/packages/QTLExperiment and https://bioconductor.org/packages/multistateQTL ).

The packages QTLExperiment and multistateQTL provide an intuitive and convenient workflow for downstream analysis of QTL summary statistics from multiple states. Together these tools can enable researchers to better understand how gene regulation differs across states, as well as discover QTLs that are unique to a subset of states. Multi-state QTL analysis can lead to the discovery of disease-relevant QTLs which may otherwise be masked in bulk QTL studies, highlighting the importance of developing open-source software tools for this purpose.