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Adapt-Mix: learning local genetic correlation structure improves summary statistics-based analyses.

Park DS, Brown B, Eng C, Huntsman S, Hu D, Torgerson DG, Burchard EG, Zaitlen N - Bioinformatics (2015)

Bottom Line: Approaches to identifying new risk loci, training risk prediction models, imputing untyped variants and fine-mapping causal variants from summary statistics of genome-wide association studies are playing an increasingly important role in the human genetics community.This approach, especially in admixed populations, has the potential to produce misleading results, ignores variation in local structure and is not feasible when appropriate reference panels are missing or small.We applied Adapt-Mix to estimate the genetic correlation structure of both admixed and non-admixed individuals using simulated and real data.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, Department of Computer Science, University of California Berkeley, Berkeley and Department of Medicine, University of California San Francisco, San Francisco, CA, USA.

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Estimated joint statistic (x axis) versus the true joint statistic (y axis) in the GALA II individuals using Σ estimated from a ‘best guess’ reference panel and Adapt-Mix. (a) Joint statistics for the GALA II Mexicans using MXL (red) and 1KG-Chrom (blue). (b) Joint statistics for the GALA II Puerto Ricans using PUR (orange) and 1KG-Chrom (blue). (c) Joint statistics for the GALA II Mexicans using MXL (red) and 1KG-No-MXL-PUR (gray). (d) Joint statistics for the GALA II Puerto Ricans using PUR (orange) and 1KG-No-MXL-PUR (gray)
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btv230-F2: Estimated joint statistic (x axis) versus the true joint statistic (y axis) in the GALA II individuals using Σ estimated from a ‘best guess’ reference panel and Adapt-Mix. (a) Joint statistics for the GALA II Mexicans using MXL (red) and 1KG-Chrom (blue). (b) Joint statistics for the GALA II Puerto Ricans using PUR (orange) and 1KG-Chrom (blue). (c) Joint statistics for the GALA II Mexicans using MXL (red) and 1KG-No-MXL-PUR (gray). (d) Joint statistics for the GALA II Puerto Ricans using PUR (orange) and 1KG-No-MXL-PUR (gray)

Mentions: In both populations, the frequencies optimized per chromosome (1KG-Chrom) performed the best. Compared with using a ‘best guess’ panel, we observed a 73.7% decrease in MSE for the Mexicans and a 70.2% decrease in MSE for the Puerto Ricans. We plotted the estimated joint statistics versus the true joint statistics for Mexicans and Puerto Ricans for different choices of Σ (Fig. 2). The results show that joint statistics computed using the combined reference panel are in higher concordance with the truth than the ‘best guess’ panel. Remarkably, even when MXL and PUR are removed from the mixture, estimates of Σ improvements can be clearly seen (Fig. 2c and d).Fig. 2.


Adapt-Mix: learning local genetic correlation structure improves summary statistics-based analyses.

Park DS, Brown B, Eng C, Huntsman S, Hu D, Torgerson DG, Burchard EG, Zaitlen N - Bioinformatics (2015)

Estimated joint statistic (x axis) versus the true joint statistic (y axis) in the GALA II individuals using Σ estimated from a ‘best guess’ reference panel and Adapt-Mix. (a) Joint statistics for the GALA II Mexicans using MXL (red) and 1KG-Chrom (blue). (b) Joint statistics for the GALA II Puerto Ricans using PUR (orange) and 1KG-Chrom (blue). (c) Joint statistics for the GALA II Mexicans using MXL (red) and 1KG-No-MXL-PUR (gray). (d) Joint statistics for the GALA II Puerto Ricans using PUR (orange) and 1KG-No-MXL-PUR (gray)
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4553832&req=5

btv230-F2: Estimated joint statistic (x axis) versus the true joint statistic (y axis) in the GALA II individuals using Σ estimated from a ‘best guess’ reference panel and Adapt-Mix. (a) Joint statistics for the GALA II Mexicans using MXL (red) and 1KG-Chrom (blue). (b) Joint statistics for the GALA II Puerto Ricans using PUR (orange) and 1KG-Chrom (blue). (c) Joint statistics for the GALA II Mexicans using MXL (red) and 1KG-No-MXL-PUR (gray). (d) Joint statistics for the GALA II Puerto Ricans using PUR (orange) and 1KG-No-MXL-PUR (gray)
Mentions: In both populations, the frequencies optimized per chromosome (1KG-Chrom) performed the best. Compared with using a ‘best guess’ panel, we observed a 73.7% decrease in MSE for the Mexicans and a 70.2% decrease in MSE for the Puerto Ricans. We plotted the estimated joint statistics versus the true joint statistics for Mexicans and Puerto Ricans for different choices of Σ (Fig. 2). The results show that joint statistics computed using the combined reference panel are in higher concordance with the truth than the ‘best guess’ panel. Remarkably, even when MXL and PUR are removed from the mixture, estimates of Σ improvements can be clearly seen (Fig. 2c and d).Fig. 2.

Bottom Line: Approaches to identifying new risk loci, training risk prediction models, imputing untyped variants and fine-mapping causal variants from summary statistics of genome-wide association studies are playing an increasingly important role in the human genetics community.This approach, especially in admixed populations, has the potential to produce misleading results, ignores variation in local structure and is not feasible when appropriate reference panels are missing or small.We applied Adapt-Mix to estimate the genetic correlation structure of both admixed and non-admixed individuals using simulated and real data.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, Department of Computer Science, University of California Berkeley, Berkeley and Department of Medicine, University of California San Francisco, San Francisco, CA, USA.

Show MeSH
Related in: MedlinePlus