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  1. ...imputation to obtain phased diploid genotypes based on SNP genotyping array data. In contrast, our work performs personalization based on the input (sequencing) data set itself and does not require a second data set. Importantly, none of the above tools use efficient imputation methods like Glimpse...
  2. ...data sets, we introduce a filtering approach called GDI that combines genotype probability (GP), alternate allele dosage (DS), and INFO score filters. We demonstrate that the imputation tools QUILT and GLIMPSE2 achieve similar accuracy, which is high enough for broad-scale ancestry mapping...
  3. OPEN ACCESS ARTICLE
  4. ...-coverage s using GLIMPSE (Rubinacci et al. 2021). With several haplotype reference panels, we compared average imputation accuracy as a function of allele frequency estimated from gnomAD AFR frequency given our small sample size. For arrays, we compared imputation accuracy using NYGC 1kGP, HGDP + 1k...
  5. ...1549-5469 1088-9051 genome;11/4/631 Errata for vol. 11, p. 319 Errata for vol. 11, p. 319 Genome Research 11: 319–324 Genomics in Latin America: Reaching the Frontiers Pablo D. Rabinowicz This paper should have been identified as a “Commentary” rather than as a “First Glimpses...
  6. ...data at a median of 5× coverage and also good 1240k data (much of this data set is available as a prepublication data release at https://reich.hms.harvard.edu/ancient--diversity-project). We used imputation with GLIMPSE (Rubinacci et al. 2021) to infer diploid genotypes at each SNP location using...
  7. ...the maintenance of a sufficient repertoire of T cell receptors to respond to a diversity of pathogens with negative selection to remove potentially autoreactive T cells (Daza-Vamenta et al. 2004). The collection of Mafa-B pseudogenes on the M3 haplotype provides a glimpse into this evolutionary balancing act...
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