نتایج جستجو برای: genome wide association study
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Pathway-based analysis is rapidly emerging as an alternative but powerful approach for searching for disease causal genes from genomic datasets and has been applied to many complex diseases recently, but it is only now beginning to be applied in psychiatry. Here, we discuss critical issues in the pathway-based approach by specifically comparing the first pathway analysis of genome-wide associat...
In genome wide association studies (GWAS), family-based studies tend to have less power to detect genetic associations than population-based studies, such as case-control studies. This can be an issue when testing if genes in a family-based GWAS have a direct effect on the phenotype of interest over and above their possible indirect effect through a secondary phenotype. When multiple SNPs are t...
Most common diseases are caused by multiple genetic and environmental factors. In the last 2 years, genome-wide association studies (GWAS) have identified polymorphisms that are associated with risk to common disease, but the effect of any one risk allele is typically small. By combining information from many risk variants, will it be possible to predict accurately each individual person's gene...
AIMS Genome-wide association studies (GWAS) have identified several risk variants for prostate cancer (pCa) mainly in Europeans, which need to be further verified in other racial groups. We selected six previously identified variants as candidates and to define the association with PCa in Northern Han Chinese. METHODS 749 subjects from Beijing and Tianjin in Northern China were included. Six ...
There are errors in the ninth, tenth and eleventh sentences of the Abstract. The correct sentences are: Individual genotyping of KLF7 rs2284932 revealed that the frequency of the minor C allele was significantly increased (P = 0.00062, Pc = 0.003, OR = 2.98, 95%CI = 1.58–5.65) in group A. The minor T allele of rs4473559 in FRMD4 demonstrated a significant association in the A group (P = 0.00015...
BACKGROUND Unnecessary intervention and overtreatment of indolent disease are common challenges in clinical management of prostate cancer. Improved tools to distinguish lethal from indolent disease are critical. METHODS We performed a genome-wide survival analysis of cause-specific death in 24,023 prostate cancer patients (3,513 disease-specific deaths) from the PRACTICAL and BPC3 consortia. ...
Incorporating Biological Pathways via a Markov Random Field Model in Genome-Wide Association Studies
Genome-wide association studies (GWAS) examine a large number of markers across the genome to identify associations between genetic variants and disease. Most published studies examine only single markers, which may be less informative than considering multiple markers and multiple genes jointly because genes may interact with each other to affect disease risk. Much knowledge has been accumulat...
Using a reduced subset of SNPs in a linear mixed model can improve power for genome-wide association studies, yet this can result in insufficient correction for population stratification. We propose a hybrid approach using principal components that does not inflate statistics in the presence of population stratification and improves power over standard linear mixed models.
Genome-wide association studies (GWAS) have identified thousands of robust and replicable genetic associations for complex disease. However, the identification of the causal variants that underlie these associations has been more difficult. This problem of fine-mapping association signals predates GWAS, but the last few years have seen a surge of studies aimed at pinpointing causal variants usi...
To search the entire human genome for association is a novel and promising approach to unravelling the genetic basis of complex genetic diseases. In these genome-wide association studies (GWAs), several hundreds of thousands of single nucleotide polymorphisms (SNPs) are analyzed at the same time, posing substantial biostatistical and computational challenges. In this paper, we discuss a number ...
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