Analyzing and comparing sequences of symbols is among the most fundamental problems in computer science, possibly even more so in bioinformatics. Maximal Common Subsequences (MCSs), i.e., inclusion-maximal sequences of non-contiguous symbols common to two or more strings, have only recently received attention in this area, despite being a basic notion and a natural generalization of more common tools like Longest Common Substrings/Subsequences. In this paper we simplify and engineer recent advancements on MCSs into a practical tool called McDag, the first publicly available tool that can index MCSs of real genomic data. We demonstrate that our tool can index sequences exceeding 10,000 base pairs within minutes, utilizing only 4-7% more than the minimum required nodes, while also extracting relevant insights.
McDag: Indexing Maximal Common Subsequences in Practice
Giovanni Buzzega;Alessio Conte;Roberto Grossi;Giulia Punzi
2024-01-01
Abstract
Analyzing and comparing sequences of symbols is among the most fundamental problems in computer science, possibly even more so in bioinformatics. Maximal Common Subsequences (MCSs), i.e., inclusion-maximal sequences of non-contiguous symbols common to two or more strings, have only recently received attention in this area, despite being a basic notion and a natural generalization of more common tools like Longest Common Substrings/Subsequences. In this paper we simplify and engineer recent advancements on MCSs into a practical tool called McDag, the first publicly available tool that can index MCSs of real genomic data. We demonstrate that our tool can index sequences exceeding 10,000 base pairs within minutes, utilizing only 4-7% more than the minimum required nodes, while also extracting relevant insights.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
