{"title":"元基因组分选问题:马尔可夫序列聚类","authors":"Grant Greenberg;Ilan Shomorony","doi":"10.1109/TMBMC.2023.3336254","DOIUrl":null,"url":null,"abstract":"The goal of metagenomics is to study the composition of microbial communities, typically using high-throughput shotgun sequencing. In the metagenomic binning problem, we observe random substrings (called contigs) from a mixture of genomes and aim to cluster them according to their genome of origin. Based on the empirical observation that genomes of different bacterial species can be distinguished based on their tetranucleotide frequencies, we model this task as the problem of clustering \n<inline-formula> <tex-math>${N}$ </tex-math></inline-formula>\n sequences generated by \n<inline-formula> <tex-math>${M}$ </tex-math></inline-formula>\n distinct Markov processes, where \n<inline-formula> <tex-math>$M \\ll N$ </tex-math></inline-formula>\n. Utilizing the large-deviation principle for Markov processes, we establish the information-theoretic limit for perfect binning. Specifically, we show that the length of the contigs must scale with the inverse of the Chernoff divergence rate between the two most similar species. Furthermore, our result implies that contigs should be binned using the KL divergence rate as a measure of distance, as opposed to the Euclidean distance often used in practice.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Metagenomic Binning Problem: Clustering Markov Sequences\",\"authors\":\"Grant Greenberg;Ilan Shomorony\",\"doi\":\"10.1109/TMBMC.2023.3336254\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The goal of metagenomics is to study the composition of microbial communities, typically using high-throughput shotgun sequencing. In the metagenomic binning problem, we observe random substrings (called contigs) from a mixture of genomes and aim to cluster them according to their genome of origin. Based on the empirical observation that genomes of different bacterial species can be distinguished based on their tetranucleotide frequencies, we model this task as the problem of clustering \\n<inline-formula> <tex-math>${N}$ </tex-math></inline-formula>\\n sequences generated by \\n<inline-formula> <tex-math>${M}$ </tex-math></inline-formula>\\n distinct Markov processes, where \\n<inline-formula> <tex-math>$M \\\\ll N$ </tex-math></inline-formula>\\n. Utilizing the large-deviation principle for Markov processes, we establish the information-theoretic limit for perfect binning. Specifically, we show that the length of the contigs must scale with the inverse of the Chernoff divergence rate between the two most similar species. Furthermore, our result implies that contigs should be binned using the KL divergence rate as a measure of distance, as opposed to the Euclidean distance often used in practice.\",\"PeriodicalId\":36530,\"journal\":{\"name\":\"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2023-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10329943/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10329943/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
The Metagenomic Binning Problem: Clustering Markov Sequences
The goal of metagenomics is to study the composition of microbial communities, typically using high-throughput shotgun sequencing. In the metagenomic binning problem, we observe random substrings (called contigs) from a mixture of genomes and aim to cluster them according to their genome of origin. Based on the empirical observation that genomes of different bacterial species can be distinguished based on their tetranucleotide frequencies, we model this task as the problem of clustering
${N}$
sequences generated by
${M}$
distinct Markov processes, where
$M \ll N$
. Utilizing the large-deviation principle for Markov processes, we establish the information-theoretic limit for perfect binning. Specifically, we show that the length of the contigs must scale with the inverse of the Chernoff divergence rate between the two most similar species. Furthermore, our result implies that contigs should be binned using the KL divergence rate as a measure of distance, as opposed to the Euclidean distance often used in practice.
期刊介绍:
As a result of recent advances in MEMS/NEMS and systems biology, as well as the emergence of synthetic bacteria and lab/process-on-a-chip techniques, it is now possible to design chemical “circuits”, custom organisms, micro/nanoscale swarms of devices, and a host of other new systems. This success opens up a new frontier for interdisciplinary communications techniques using chemistry, biology, and other principles that have not been considered in the communications literature. The IEEE Transactions on Molecular, Biological, and Multi-Scale Communications (T-MBMSC) is devoted to the principles, design, and analysis of communication systems that use physics beyond classical electromagnetism. This includes molecular, quantum, and other physical, chemical and biological techniques; as well as new communication techniques at small scales or across multiple scales (e.g., nano to micro to macro; note that strictly nanoscale systems, 1-100 nm, are outside the scope of this journal). Original research articles on one or more of the following topics are within scope: mathematical modeling, information/communication and network theoretic analysis, standardization and industrial applications, and analytical or experimental studies on communication processes or networks in biology. Contributions on related topics may also be considered for publication. Contributions from researchers outside the IEEE’s typical audience are encouraged.