Project description:Genome-wide association studies (GWAS) are instrumental in identifying loci with an impact on human traits and disease. Typically, however, most GWAS information is considered redundant as it is based on neighboring single-nucleotide variants (SNVs) in strong linkage disequilibrium (LD). In this context, besides the most significant hit (lead SNV) in every trait- or disease-associated locus, the rest of GWAS hits are often marginally reported, examined, or exploited. To interrogate the value of integrating the information provided by the full set of GWAS hits and fine-mapping haplotypes containing these SNVs, here we focused on a locus repeatedly associated with traits of the cardiac electrical conduction system and arrhythmia (SCN5A-SCN10A). We found that the same SNV can exhibit differing associations depending on haplotype. Thus, these analyses provide corroborative evidence that assuming redundancy among neighboring GWAS hits has the risk of missing critical disease-risk associations.
Project description:Evaluation of short-read-only, long-read-only, and hybrid assembly approaches on metagenomic samples demonstrating how they affect gene and protein prediction which is relevant for downstream functional analyses. For a human gut microbiome sample, we use complementary metatranscriptomic, and metaproteomic data to evaluate the metagenomic-based protein predictions.