LAUSR

Background Genome-Wide Association Studies (GWASs) provide a wealth of information that can serve as a backbone for making biological inferences. There are over 160 loci reported with genome-wide significant association with Schizophrenia (SZ) and Bipolar Disorder (BD), and thousands more nominally associated loci that contribute to risk (Purcell et al., 2009; Welter et al., 2014). SNPs with the strongest association to SZ and BD are predominately in non-coding DNA, thus it is often challenging to decipher the function of risk SNPs. Functional and regulatory maps from the ENCODE and Roadmap projects offer detailed annotations of the genome, which can help bridge the gap between GWAS signals and biological mechanisms. We present a new software tool called Functional LD-clump EnrichmEnt Test (FLEET) to decode the underlying biology of GWAS signals via overlaying information from the ENCODE and Roadmap Projects. Possible utilities of this software include: prioritizing risk genes for fine-mapping, illuminating potential regulatory mechanisms that underlie susceptibility, and identifying molecular substrates that are common to psychiatric disorders. Methods FLEET is available for download on Github (https://github.com/hessJ/FLEET). FLEET is currently adapted as a modular script written in R and is under active development. Users must supply a file of genome-wide association summary statistics and modify a few flags in FLEET to run the analysis properly. FLEET performs data reformatting, GWAS pruning, SNP-to-annotation mapping, statistical analyses (i.e., weighted linear regression and permutations), and plotting of results. Results GWAS results of SZ (Ripke et al., 2014) and BD (Hou et al., 2016) revealed widespread associations with histone markers and DNA accessibility in brain, immune and other peripheral tissues. In addition, significant enrichment was detected for gene sets that participate in neurotransmission and neurodevelopment, histone modification enzymes, and target sites of transcription factors, microRNAs, and RNA-binding proteins. Discussion Our software provides unique insight into the underlying biology of SZ and BD risk signals and a framework for hypothesis generation. FLEET is a flexible and efficient pipeline for analyzing biological relationships among GWASs of complex polygenic disorders. FLEET is capable of modeling genome-wide enrichment statistics and performing permutation tests on top GWAS markers; both tests include adjustments for confounding variation (i.e., LD and minor allele frequency). This software is included with a pre-formatted database of >5,800 annotations, and users can provide custom annotations for analysis.