Abstract

BackgroundHaplotype assembly is the process of assigning the different alleles of the variants covered by mapped sequencing reads to the two haplotypes of the genome of a human individual. Long reads, which are nowadays cheaper to produce and more widely available than ever before, have been used to reduce the fragmentation of the assembled haplotypes since their ability to span several variants along the genome. These long reads are also characterized by a high error rate, an issue which may be mitigated, however, with larger sets of reads, when this error rate is uniform across genome positions. Unfortunately, current state-of-the-art dynamic programming approaches designed for long reads deal only with limited coverages.ResultsHere, we propose a new method for assembling haplotypes which combines and extends the features of previous approaches to deal with long reads and higher coverages. In particular, our algorithm is able to dynamically adapt the estimated number of errors at each variant site, while minimizing the total number of error corrections necessary for finding a feasible solution. This allows our method to significantly reduce the required computational resources, allowing to consider datasets composed of higher coverages. The algorithm has been implemented in a freely available tool, HapCHAT: Haplotype Assembly Coverage Handling by Adapting Thresholds. An experimental analysis on sequencing reads with up to 60 × coverage reveals improvements in accuracy and recall achieved by considering a higher coverage with lower runtimes.ConclusionsOur method leverages the long-range information of sequencing reads that allows to obtain assembled haplotypes fragmented in a lower number of unphased haplotype blocks. At the same time, our method is also able to deal with higher coverages to better correct the errors in the original reads and to obtain more accurate haplotypes as a result.AvailabilityHapCHAT is available at http://hapchat.algolab.euunder the GNU Public License (GPL).

Highlights

  • Haplotype assembly is the process of assigning the different alleles of the variants covered by mapped sequencing reads to the two haplotypes of the genome of a human individual

  • Availability: Haplotype Assembly Coverage Handling by Adapting (HapCHAT) is available at http://hapchat.algolab.eu under the GNU’s Not Unix (GNU) Public License (GPL)

  • We report the results obtained by running the tools with maximum coverage 30× for HapCHAT, 25× for HapCol, 15× and 20× for WhatsHap

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Summary

Introduction

Haplotype assembly is the process of assigning the different alleles of the variants covered by mapped sequencing reads to the two haplotypes of the genome of a human individual. Due to the availability of curated, high quality haplotype reference panels on a large population of individuals [8, 9], computational methods for statistically inferring the haplotypes of an individual from these panels are widely used [1, 10] The accuracy of these methods, depends heavily on the size and diversity of the population used to compile the panels, entailing poor performance on rare variants, while de novo variants are completely missed. These types of variants appear in the sequencing reads of the individual, making read-based haplotype assembly the obvious solution

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