Improved whole-chromosome phasing for disease and population genetic studies

By Olivier Delaneau, Jean-François Zagury, Jonathan Marchini. Nature Methods, 2013

535 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0f09fa093529587b164164932a2a7b86f9cb56f8

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In Genetics

Citations in the corpus

Robust and scalable inference of population history from hundreds of unphased whole-genomes (2016, background): “The other two contained artificially induced switch errors at rates of 1% and 5%, which are approximate upper and lower bounds on the accuracy of existing phasing algorithms 29,30 .”
HapCUT2: robust and accurate haplotype assembly for diverse sequencing technologies (2017, methodology): “Recently, a population phasing method, SHAPEIT2, has been extended to incorporate information from haplotype-in-formative sequence reads in the statistical model for phasing using population haplotypes (Delaneau et al. 2013).”
Fast and accurate long-range phasing in a UK Biobank cohort (2015, unknown): “, 14x faster than SHAPEIT2 [12]).”
Integrating sequence and array data to create an improved 1000 Genomes Project haplotype reference panel (2014, methodology): “For this reason SHAPEIT2 is among the most computationally tractable methods [7, 8].”
Inferring human population size and separation history from multiple genome sequences (2014, unknown): “All segregating sites that are present in the 1000 Genomes integrated variant call set were phased with the SHAPEIT2 software [47] using the 1000 Genomes reference panel [48].”
Haplotype estimation using sequencing reads. (2013, methodology): “Supplemental Data includes Figure S1 and Table S1 and can be found with this article online at http://www.cell.com/AJHG.”
Genome-Wide Inference of Ancestral Recombination Graphs (2013, methodology): “We phased the data using SHAPEIT v2 [59], guided by the pedigree information describing the relationships among the 69 individuals.”
Fast two-stage phasing of large-scale sequence data. (2021, methodology): “…came from incorporating methodological ideas from genotype imputation and from data compression, such as the use of a small, custom reference panel for each individual, 24,25 and from the use of the positional Burrows-Wheeler transform 26 for efﬁciently identifying long shared allele sequences.”
A General Approach for Haplotype Phasing across the Full Spectrum of Relatedness (2014, methodology): “We recently compared several methods all designed to phase nominally unrelated samples (SHAPEIT2 [2], SHAPEIT1 [5], Beagle [4], HAPI-UR [6], Impute2 [24], MaCH [25], fastPHASE [26]) and found that SHAPEIT2 was the most accurate method in this setting.”