{"title":"An Algorithm to Calculate the <i>p</i>-Value of the Monge-Elkan Distance.","authors":"Petr Ryšavý, Filip Železný","doi":"10.1089/cmb.2024.0854","DOIUrl":null,"url":null,"abstract":"<p><p>The Monge-Elkan distance is a straightforward yet popular distance measure used to estimate the mutual similarity of two sets of objects. It was initially proposed in the field of databases, and it found broad usage in other fields. Nowadays, it is especially relevant to the analysis of new-generation sequencing data as it represents a measure of dissimilarity between genomes of two distinct organisms, particularly when applied to unassembled reads. This article provides an algorithm to calculate the <i>p</i>-value associated with the Monge-Elkan distance. Given the object-level null distribution, that is, the distribution of distances between independently and identically sampled objects such as reads, the method yields the null distribution of the Monge-Elkan distance, which in turn allows for calculating the <i>p</i>-value. We also demonstrate an application on sequencing data, where individual reads are compared by the Levenshtein distance.</p>","PeriodicalId":15526,"journal":{"name":"Journal of Computational Biology","volume":" ","pages":""},"PeriodicalIF":1.4000,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computational Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1089/cmb.2024.0854","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
The Monge-Elkan distance is a straightforward yet popular distance measure used to estimate the mutual similarity of two sets of objects. It was initially proposed in the field of databases, and it found broad usage in other fields. Nowadays, it is especially relevant to the analysis of new-generation sequencing data as it represents a measure of dissimilarity between genomes of two distinct organisms, particularly when applied to unassembled reads. This article provides an algorithm to calculate the p-value associated with the Monge-Elkan distance. Given the object-level null distribution, that is, the distribution of distances between independently and identically sampled objects such as reads, the method yields the null distribution of the Monge-Elkan distance, which in turn allows for calculating the p-value. We also demonstrate an application on sequencing data, where individual reads are compared by the Levenshtein distance.
期刊介绍:
Journal of Computational Biology is the leading peer-reviewed journal in computational biology and bioinformatics, publishing in-depth statistical, mathematical, and computational analysis of methods, as well as their practical impact. Available only online, this is an essential journal for scientists and students who want to keep abreast of developments in bioinformatics.
Journal of Computational Biology coverage includes:
-Genomics
-Mathematical modeling and simulation
-Distributed and parallel biological computing
-Designing biological databases
-Pattern matching and pattern detection
-Linking disparate databases and data
-New tools for computational biology
-Relational and object-oriented database technology for bioinformatics
-Biological expert system design and use
-Reasoning by analogy, hypothesis formation, and testing by machine
-Management of biological databases