Abstract
Genome-wide association study (GWAS), exploring the historical and evolutionary recombinations at the population level, is a major method adopted to identify quantitative trait loci (QTL) for complex traits. However, to summarize GWAS results, gene structure, and linkage disequilibrium (LD) in a single view, multiple tools are required. It is tedious to generate these three results and manually put them together; moreover, it may eventually lead to inaccuracies. On the other hand, genotype markers are usually detected by DNA- and/or RNA-Seq. For GWAS analysis based on RNA-Seq, markers from DNA-Seq provide more genetic information when displaying LD. The currently released software package does not have this function for an integrated analysis of LD, using genotypic markers different from that in association analysis. Here, we present an R package, IntAssoPlot, which provides an integrated visual display of GWAS results, along with LD and gene structure information, in a publication-ready format. The main panel of an IntAssoPlot plot has a connecting line linking the genome-wide association P-values on the -log10 scale with the gene structure and LD matrix. Importantly, IntAssoPlot is designed to plot GWAS results with LD calculated from genotypes different from those in GWAS analysis. IntAssoPlot provides a powerful visualization tool to gain an integrated insight into GWAS results. The functions provided by IntAssoPlot increase the efficiency by revealing GWAS results in a publication-ready format. Inspection of the output image can provide important biological information, including the loci that passed the genome-wide significance threshold, genes located at or near the significant loci, and the extent of LD within the selected region.
Highlights
During the past few years, a sufficient number of molecular markers and availability of fast and accurate variance component estimation methods have made Genome-wide association study (GWAS) an ideal tool to detect genetic relationships with complex traits (Mackay, 2001; Yu and Buckler, 2006; Wang and Qin, 2017)
For the GWAS results calculated from single nucleotide polymorphism (SNP) detected by RNA-Seq, it is necessary, though difficult, to display GWAS results with linkage disequilibrium (LD) calculated from genome-wide SNPs by re-sequencing
The output image of an IntAssoPlot plot, which is in a publication-ready format, draws a line connecting the P-values on a -log10 scale, the genome annotation, and the LD matrix, calculated from genotypes same or different from those in GWAS analysis
Summary
During the past few years, a sufficient number of molecular markers and availability of fast and accurate variance component estimation methods have made GWAS an ideal tool to detect genetic relationships with complex traits (Mackay, 2001; Yu and Buckler, 2006; Wang and Qin, 2017). To efficiently visualize GWAS results, packages such as LocusZoom, cgmisc, Ldlink, and Assocplots have been developed (Pruim et al, 2010; Kierczak et al, 2015; Machiela and Chanock, 2015; Khramtsova and Stranger, 2017). The tools for visualizing GWAS results should represent information detailing (1) the loci passing the genome-wide significance threshold, (2) the genes present at or near the significant loci, and (3) the linkage disequilibrium (LD) structure of the significant loci. Even though the LocusZoom and cgmisc can display regional GWAS information, such as the association of signal relative to genomic position and LD (LD between the most significant associated loci with the rest), no connecting line linking the significant loci, gene structure, and LD matrix is shown. For the GWAS results calculated from SNPs detected by RNA-Seq, it is necessary, though difficult, to display GWAS results with LD calculated from genome-wide SNPs by re-sequencing
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
