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HaploJuice : accurate haplotype assembly from a pool of sequences with known relative concentrations

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Wong, Thomas
Ranjard, Louis
Lin, Yu
Rodrigo, Allen

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BioMed Central

Abstract

Pooling techniques, where multiple sub-samples are mixed in a single sample, are widely used to take full advantage of high-throughput DNA sequencing. Recently, Ranjard et al. [1] proposed a pooling strategy without the use of barcodes. Three sub-samples were mixed in different known proportions (i.e. 62.5%, 25% and 12.5%), and a method was developed to use these proportions to reconstruct the three haplotypes effectively. HaploJuice provides an alternative haplotype reconstruction algorithm for Ranjard et al.’s pooling strategy. HaploJuice significantly increases the accuracy by first identifying the empirical proportions of the three mixed sub-samples and then assembling the haplotypes using a dynamic programming approach. HaploJuice was evaluated against five different assembly algorithms, Hmmfreq [1], ShoRAH [2], SAVAGE [3], PredictHaplo [4] and QuRe [5]. Using simulated and real data sets, HaploJuice reconstructed the true sequences with the highest coverage and the lowest error rate. HaploJuice achieves high accuracy in haplotype reconstruction, making Ranjard et al.’s pooling strategy more efficient, feasible, and applicable, with the benefit of reducing the sequencing cost.

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BMC Bioinformatics

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Open Access

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Creative Commons Attribution 4.0 International License

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