Related papers: GWGGI: software for genome-wide gene-gene interact…
Common complex diseases are likely influenced by the interplay of hundreds, or even thousands, of genetic variants. Converging evidence shows that genetic variants with low marginal effects (LME) play an important role in disease…
Genome-wide association studies generate very large datasets that require scalable analysis algorithms. In this report we describe the GEDI software package, which implements efficient algorithms for performing several common tasks in the…
Motivation: The availability of thousands of invidual genomes of one species should boost rapid progress in personalized medicine or understanding of the interaction between genotype and phenotype, to name a few applications. A key…
With the recent advent of high-throughput genotyping techniques, genetic data for genome-wide association studies (GWAS) have become increasingly available, which entails the development of efficient and effective statistical approaches.…
Gene-gene interactions have long been recognized to be fundamentally important to understand genetic causes of complex disease traits. At present, identifying gene-gene interactions from genome-wide case-control studies is computationally…
Gene-gene interactions play a crucial role in the manifestation of complex human diseases. Uncovering significant gene-gene interactions is a challenging task. Here, we present an innovative approach utilizing data-driven computational…
Through genome-wide association studies (GWAS), disease susceptible genetic variables can be identified by comparing the genetic data of individuals with and without a specific disease. However, the discovery of these associations poses a…
Summary: With the rapid development of long-read sequencing technologies, the era of individual complete genomes is approaching. We have developed wgatools, a cross-platform, ultrafast toolkit that supports a range of whole genome alignment…
Modern DNA sequencing technologies enable geneticists to rapidly identify genetic variation among many human genomes. However, isolating the minority of variants underlying disease remains an important, yet formidable challenge for medical…
The variance component tests used in genomewide association studies of thousands of individuals become computationally exhaustive when multiple traits are analysed in the context of omics studies. We introduce two high-throughput algorithms…
Much of the natural variation for a complex trait can be explained by variation in DNA sequence levels. As part of sequence variation, gene-gene interaction has been ubiquitously observed in nature, where its role in shaping the development…
Motivation: The three-dimensional (3D) organization of the genome plays a critical role in regulating gene expression and maintaining cellular homeostasis. Disruptions in this spatial organization can result in abnormal chromatin…
Non-sharable sensitive data collection and analysis in large-scale consortia for genomic research is complicated. Time consuming issues in installing software arise due to different operating systems, software dependencies and running the…
A computational challenge to validate the candidate disease genes identified in a high-throughput genomic study is to elucidate the associations between the set of candidate genes and disease phenotypes. The conventional gene set enrichment…
Identification of genes that initiate cell anomalies and cause cancer in humans is among the important fields in the oncology researches. The mutation and development of anomalies in these genes are then transferred to other genes in the…
Genome-wide association studies (GWAS) have identified hundreds of loci at very stringent levels of statistical significance across many different human traits. However, it is now clear that very large samples (n~10^4-10^5) are needed to…
Increasing evidence has shown that gene-gene interactions have important effects on biological processes of human diseases. Due to the high dimensionality of genetic measurements, existing interaction analysis methods usually suffer from a…
Motivation: Modern bioinformatics workflows, particularly in imaging and representation learning, can generate thousands to tens of thousands of quantitative phenotypes from a single cohort. In such settings, running genome-wide association…
Gene/protein interactions provide critical information for a thorough understanding of cellular processes. Recently, considerable interest and effort has been focused on the construction and analysis of genome-wide gene networks. The large…
Popular online enrichment analysis tools from the field of molecular systems biology provide users with the ability to submit their experimental results as gene sets for individual analysis. Such queries are kept private, and have never…