Safety in Multi-Assembly via Paths Appearing in All Path Covers of a DAG

• Published in: IEEE/ACM transactions on computational biology and bioinformatics Vol. 19; no. 6; pp. 3673 - 3684
• Main Authors: Caceres, Manuel, Mumey, Brendan, Husic, Edin, Rizzi, Romeo, Cairo, Massimo, Sahlin, Kristoffer, Tomescu, Alexandru I.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01-11-2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Analysis of Algorithms and Problem Complexity; Annotations; Apexes; Assembly; Base Sequence; Bioinformatics; Biology and genetics; Computer Science; Constraints; datalogi; Genome; Genomics; Graph algorithms; Graph theory; Network problems; RNA; Safety; Sequential analysis; Splicing
• ISSN: 1545-5963; 1557-9964; 1557-9964
• DOI: 10.1109/TCBB.2021.3131203

A multi-assembly problem asks to reconstruct multiple genomic sequences from mixed reads sequenced from all of them. Standard formulations of such problems model a solution as a path cover in a directed acyclic graph, namely a set of paths that together cover all vertices of the graph. Since multi-assembly problems admit multiple solutions in practice, we consider an approach commonly used in standard genome assembly: output only partial solutions ( contigs , or safe paths ), that appear in all path cover solutions. We study constrained path covers, a restriction on the path cover solution that incorporate practical constraints arising in multi-assembly problems. We give efficient algorithms finding all maximal safe paths for constrained path covers. We compute the safe paths of splicing graphs constructed from transcript annotations of different species. Our algorithms run in less than 15 seconds per species and report RNA contigs that are over 99% precise and are up to 8 times longer than unitigs. Moreover, RNA contigs cover over 70% of the transcripts and their coding sequences in most cases. With their increased length to unitigs, high precision, and fast construction time, maximal safe paths can provide a better base set of sequences for transcript assembly programs.