Ariadne: synthetic long read deconvolution using assembly graphs

Abstract

AbstractSynthetic long read sequencing techniques such as UST’s TELL-Seq and Loop Genomics’ LoopSeq combine 3$$'$$ ′ barcoding with standard short-read sequencing to expand the range of linkage resolution from hundreds to tens of thousands of base-pairs. However, the lack of a 1:1 correspondence between a long fragment and a 3$$'$$ ′ unique molecular identifier confounds the assignment of linkage between short reads. We introduce Ariadne, a novel assembly graph-based synthetic long read deconvolution algorithm, that can be used to extract single-species read-clouds from synthetic long read datasets to improve the taxonomic classification and de novo assembly of complex populations, such as metagenomes.