Title | Ariadne: synthetic long read deconvolution using assembly graphs. |
Publication Type | Journal Article |
Year of Publication | 2023 |
Authors | Mak L, Meleshko D, Danko DC, Barakzai WN, Maharjan S, Belchikov N, Hajirasouliha I |
Journal | Genome Biol |
Volume | 24 |
Issue | 1 |
Pagination | 197 |
Date Published | 2023 Aug 28 |
ISSN | 1474-760X |
Keywords | Algorithms, Genomics, Metagenome, Pentaerythritol Tetranitrate |
Abstract | Synthetic long read sequencing techniques such as UST's TELL-Seq and Loop Genomics' LoopSeq combine 3[Formula: see text] 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[Formula: see text] 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. |
DOI | 10.1186/s13059-023-03033-5 |
Alternate Journal | Genome Biol |
PubMed ID | 37641111 |
PubMed Central ID | PMC10463629 |
Grant List | R35 GM138152 / GM / NIGMS NIH HHS / United States T32 GM083937 / GM / NIGMS NIH HHS / United States |