![after effects 2014 v8 after effects 2014 v8](https://assets.rocketstock.com/uploads/2016/03/GIF-01-Cycle1.gif)
This can be problematic when genes are differentially expressed in ancestral populations of admixed individuals. The potential disadvantage of correcting only for GA is that it does not precisely account for ancestry at any specific locus. This approach has the advantage of averaging genomic background effects and was used in eQTL mapping for the main GTEx releases. Global ancestry (GA), or the proportions of different ancestral populations represented across the entire genome, is routinely used to adjust for population structure in genetic association studies.
![after effects 2014 v8 after effects 2014 v8](https://www.gfxtra31.com/uploads/posts/2018-04/1524631133_99-4_500x281.png)
Such substructure can confound genetic associations, and insufficient control may increase spurious findings. Genetic studies with individuals of admixed ancestries may suffer from additional challenges due to complex population substructure.
![after effects 2014 v8 after effects 2014 v8](https://i1.wp.com/latestadobe.com/wp-content/uploads/2020/07/after-effects-cc-2014-free-download.png)
While the majority of such studies focus on single-ancestry populations or relatively homogeneous populations, the latest Genotype-Tissue Expression (GTEx) project (v8) includes up to 17% of individuals with non-European or admixed ancestry. Subsequently, large-scale expression quantitative trait loci (eQTL) datasets are studied to provide insights for genetic variants associated with complex traits. Thousands of genome-wide association studies (GWAS) have been published to date. While the majority of the results are concordant between local and global ancestry-based adjustments, we identify distinct advantages and disadvantages to each approach. We provide a local ancestry map for admixed individuals in the GTEx v8 release and describe the impact of ancestry and admixture on gene expression, eQTLs, and GWAS colocalization. Finally, we identify a small subset of eQTL-associated variants highly correlated with local ancestry, providing a resource to enhance functional follow-up. Notably, both adjustments produce similar numbers of significant colocalizations within each of two different colocalization methods, COLOC and FINEMAP. At loci where the two adjustments produce different lead variants, we observe 31 loci (0.02%) where a significant colocalization is called only with one eQTL ancestry adjustment method. Consistent with previous work, we observe improved power with local ancestry adjustment.
![after effects 2014 v8 after effects 2014 v8](https://getgamez.net/wp-content/uploads/2019/05/After-Effects-CC-2018-for-free.jpg)
We perform genome-wide cis-eQTL mapping using admixed samples in seven tissues, adjusted by either global or local ancestry. Here, we identify a subset of 117 individuals in GTEx (v8) with a high degree of population admixture and estimate genome-wide local ancestry. Assessing ancestry-based adjustments in GTEx improves portability of this research across populations and further characterizes the impact of population structure on GWAS colocalization. The Genotype-Tissue Expression (GTEx) project largely contains individuals of European ancestry, but the v8 release also includes up to 15% of individuals of non-European ancestry. Population structure among study subjects may confound genetic association studies, and lack of proper correction can lead to spurious findings.