Sentence examples for mapping of causal from inspiring English sources

In this review, we highlight some of the key advances from the recent literature in which transethnic GWASs have been used for locus discovery, replication, fine-mapping or admixture mapping of causal variants associated with complex diseases.

Integration of low- and high-resolution eQTL data is a feasible strategy for computational fine mapping of causal genes.

The mapping of causal variants for complex disease traits requires the correctly assigned physical order and orientation of genomic sequences, and genetic relationship among genetic markers in specific genomic regions (LD status and functional annotation), which is still under development for pig genomics researchers now [23], [36].

The rapid decay of LD by distance in crossbred populations can be useful for high-resolution mapping of causal polymorphisms.

The differential and lower level of LD in African Americans will likely greatly improve the fine mapping of causal variants in ongoing trans-ancestry meta-analysis efforts.

High density genetic markers are crucial for fine mapping of causal variation that may contribute to quality improvement in rice cultivars and crop breeding [ 7, 47].

In Investigation 2, it was seen that when a very large number of voxels is considered as potential source locations, PDC can provide a map of causal areas in which also caused areas might appear because of ghost causality connections identified by PDC.

We suggest that the application of genome-wide selection scans and GWAS using larger resource populations with phenotypic information can further improve the fine-mapping of causal mutations controlling complex traits.

With the increasing availability of GWAS data from diverse populations, transethnic meta-analysis may offer an exciting opportunity to increase the power to detect novel loci, through increased sample size, as well as to improve the resolution of fine-mapping of causal variants [Cooper et al., 2008; Zaitlen et al., 2010].

With the increasing availability of genomewide association data from diverse populations, transethnic meta-analysis may offer an exciting opportunity to increase the power to detect novel complex trait loci and to improve the resolution of fine-mapping of causal variants by leveraging differences in local linkage disequilibrium structure between ethnic groups.

However, a similar map of causal areas cannot be constructed based on PDC.