WgLink: reconstructing whole-genome viral haplotypes using L0+L1-regularization.

SUMMARY

Many tools can reconstruct viral sequences based on next-generation sequencing reads. Although existing tools effectively recover local regions, their accuracy suffers when reconstructing the whole viral genomes (strains). Moreover, they consume significant memory when the sequencing coverage is high or when the genome size is large. We present WgLink to meet this challenge. WgLink takes local reconstructions produced by other tools as input and patches the resulting segments together into coherent whole-genome strains. We accomplish this using an L0+L1-regularized regression, synthesizing variant allele frequency data with physical linkage between multiple variants spanning multiple regions simultaneously. WgLink achieves higher accuracy than existing tools both on simulated and on real datasets while using significantly less memory (RAM) and fewer CPU hours.

AVAILABILITY AND IMPLEMENTATION

Source code and binaries are freely available at https://github.com/theLongLab/wglink.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.