MTG-Link: leveraging barcode information from linked-reads to assemble specific loci - Archive ouverte HAL
Pré-Publication, Document De Travail (Preprint/Prepublication) Année : 2022

MTG-Link: leveraging barcode information from linked-reads to assemble specific loci

Résumé

Background: Local assembly with short and long reads has proven to be very useful in many applications: reconstruction of the sequence of a locus of interest, gap-filling in draft assemblies, as well as alternative allele reconstruction of large insertion variants. Whereas linked-read technologies have a great potential to assemble specific loci as they provide long-range information while maintaining the power and accuracy of short-read sequencing, there is a lack of local assembly tools for linked-read data. Results: We present MTG-Link, a novel local assembly tool dedicated to linked-reads. The originality of the method lies in its read subsampling step which takes advantage of the barcode information contained in linked-reads mapped in flanking regions. We validated our approach on several datasets from different linked-read technologies. We show that MTG-Link is able to assemble successfully large sequences, up to dozens of Kb. We also demonstrate that the read subsampling step of MTG-Link considerably improves the local assembly of specific loci compared to other existing short-read local assembly tools. Furthermore, MTG-Link was able to fully characterize large insertion variants in a human genome and improved the contiguity of a 1.3 Mb locus of biological interest in several individual genomes of the mimetic butterfly ( Heliconius numata ). Conclusions: MTG-Link is an efficient local assembly tool designed for different linked-read sequencing technologies. MTG-Link source code is available at https://github.com/anne-gcd/MTG-Link and as a Bioconda package.
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hal-03886951 , version 1 (06-12-2022)

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Anne Guichard, Fabrice Legeai, Denis Tagu, Claire Lemaitre. MTG-Link: leveraging barcode information from linked-reads to assemble specific loci. 2022. ⟨hal-03886951⟩
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