I'm wondering if imputation, specifically Beagle, needs a reference panel that matches the sample's ancestry group. For example, Beagle documentation suggests the 1000 Genomes Project phase 3 reference panel, which contains all ancestry groups. Is this acceptable to use to impute the genome of, say, an East Asian, African, and European?
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2 Answers
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Basically, yes, you will get better results if you use a reference panel which contains samples with similar ancestry to your targets. Imputation works by matching haplotypes in your target samples to those in a reference panel. If the haplotypes in the target don’t exist in the reference panel, the variants won’t be imputed accurately.
We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations[Hispanic/Latino and African], which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11-34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels.
From this paper.
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$\begingroup$ Is it still acceptable to use a general reference panel like 1000 Genomes Project Phase 3, or has everyone switched to ancestry-specific by now? $\endgroup$ May 29 at 17:56
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$\begingroup$ Most people use TopMed now using a remote server, or use their own custom ancestry specific one, I don’t think many serious studies use 1000 genomes anymore $\endgroup$ May 29 at 18:03
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$\begingroup$ TopMed is similar to 1000 genomes in that they are multiethnic. I agree that TopMed is better for other reasons. However, the question of "does a multiethnic panel which includes some samples of ethnicity X improves accuracy for ethnicity X over a panel without ethnicity X?" is a different question than "if the panel consisted of only ethnicity X, would that improve accuracy over the multiethnic panel?" $\endgroup$ May 29 at 22:10
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$\begingroup$ Well yes as the abstract says, E.g. Latino ancestry individuals are imputed better using topmed because they it contains Latino samples. You can only get good imputation of non-common variants if you have individuals of matched ancestry in the reference panel. $\endgroup$ May 29 at 22:21
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1$\begingroup$ @BigMistake Jonathan Marchini did 1000g imputation. He observed that pooling all samples together achieved accuracy than imputing in individual populations independently. Don't split by population. $\endgroup$ May 30 at 16:41
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in my experience you should use a publicly cited reference genome like GRCh37 or GRCh38
https://www.sciencedirect.com/science/article/pii/S0888754317300058
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1$\begingroup$ I use GRCh37 but I need to use a reference panel in addition to a reference genome $\endgroup$ May 23 at 20:32
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1$\begingroup$ The question asks about a reference panel, not a reference genome. $\endgroup$ May 24 at 8:49