Code and data accompanying SuSiE manuscript (Wang et al, 2018)


This repository contains code and data resources to accompany our research paper:

Gao Wang, Abhishek Sarkar, Peter Carbonetto, Matthew Stephens (2018). A new variational approach to variable selection in regression, with applications to fine-mapping genetic associations. (in preparation)

We provide three sets of resources:

  1. If you are primarily interested in applying SuSiE to your own data in a generic setting, please see the susieR package. A good place to start is the vignettes page. Though stemmed from the context of genetic fine-mapping, the notebook here to reproduce the pedagogical example used in our paper may also be useful in understanding the motivation and design of SuSiE model.

  2. If you would like to reproduce the numerical studies in comparison with fine-mapping methods CAVIAR, FINEMAP and DAP-G, please see here for an implementation in the Dynamic Statistical Comparison framework, and here to reproduce figures in the "numerical studies" section of the manuscript.

  3. If you would like to use SuSiE for fine-mapping of molecular traits similar to our data application of association analysis of splice QTL data please see our analysis of Li et al 2016 data for details: we provide a generic pipeline for fine-mapping with SuSiE and a splice QTL enrichment analysis pipeline for SuSiE signals in functional regions in genome. Although not used by the manuscript there is an additional enrichment pipeline we provide for matched analysis for other molecular QTLs as suggested in Li et al 2016. A series of commandlines were provided to reproduce the data application section of the manuscript using these pipelines.

Citing this repository

If you find any of the source code in this repository useful for your work, please cite our manuscript, Wang et al (2018). The full citation is given above. Please also cite the Zenodo archive for this repository:

Gao Wang, Abhishek Sarkar, Peter Carbonetto and Matthew Stephens (2018), Code and data accompanying SuSiE manuscript (Wang et al, 2018), version 1.0, Zenodo, doi:10.xxxx/zenodo.xxxxx.


Copyright (c) 2017-2018, Gao Wang, Abhishek Sarkar, Peter Carbonetto and Matthew Stephens.

All source code and software in this repository are made available under the terms of the MIT license.

© 2017-2018 authored by Gao Wang at Stephens Lab, The University of Chicago