A machine-compiled database of genome-wide association studies
نویسندگان
چکیده
منابع مشابه
Machine learning in genome-wide association studies.
Recently, genome-wide association studies have substantially expanded our knowledge about genetic variants that influence the susceptibility to complex diseases. Although standard statistical tests for each single-nucleotide polymorphism (SNP) separately are able to capture main genetic effects, different approaches are necessary to identify SNPs that influence disease risk jointly or in comple...
متن کاملMachine Learning for Genome - Wide Association Studies : A Critical Review
The finalisation of the Human Genome Project in April 2003, when a complete sequence was published for the first time, created the potential to identify a large set of single nucleotide polymorphisms (SNPs) across the entire genome. Consequently, this has opened the door to possibilities for great improvements in diagnosis and therapeutics (Hirschorn & Daly 2005). In the years following the Hum...
متن کاملGenome-wide Association Studies
Progress in probabilistic generative models has accelerated, developing richer models with neural architectures, implicit densities, and with scalable algorithms for their Bayesian inference. However, there has been limited progress in models that capture causal relationships, for example, how individual genetic factors cause major human diseases. In this work, we focus on two challenges in par...
متن کاملGenome-wide Association Studies
Progress in probabilistic generative models has accelerated, developing richer models with neural architectures, implicit densities, and with scalable algorithms for their Bayesian inference. However, there has been limited progress in models that capture causal relationships, for example, how individual genetic factors cause major human diseases. In this work, we focus on two challenges in par...
متن کاملGenome-wide association studies.
Genome-wide association (GWA) studies are best understood as an extension of candidate gene association studies, scaled up to cover hundreds of thousands of markers across the genome in samples usually of several thousand cases and controls. The GWA approach allows the detection of much smaller effect sizes than with previous linkage-based genome-wide studies. However, this sensitivity makes th...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Nature Communications
سال: 2019
ISSN: 2041-1723
DOI: 10.1038/s41467-019-11026-x