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To identify disease-associated bacteria (markers), a typical method is to statistically compare the relative abundance of bacteria between healthy subjects and diseased patients. However, since bacteria do not necessarily cause diseases in isolation, it is also important to focus on the interactions and relationships among bacteria when examining their association with diseases. In fact, although there are common approaches to represent and analyze bacterial interaction relationships as networks, there are limited methods to find bacteria associated with diseases through network-driven analysis. In this paper, we focus on rewiring of the bacterial network and propose a new method for quantifying the rewiring. We then apply the proposed method to a group of colorectal cancer patients. We show that it can identify and detect bacteria that cannot be detected by conventional methods such as abundance comparison. Furthermore, the proposed method is implemented as a general-purpose tool and made available to the general public.<\/jats:p>","DOI":"10.1186\/s12859-024-05702-z","type":"journal-article","created":{"date-parts":[[2024,3,18]],"date-time":"2024-03-18T10:02:28Z","timestamp":1710756148000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["QNetDiff: a quantitative measurement of network rewiring"],"prefix":"10.1186","volume":"25","author":[{"given":"Shota","family":"Nose","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hirotsugu","family":"Shiroma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Takuji","family":"Yamada","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yushi","family":"Uno","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,3,18]]},"reference":[{"issue":"4","key":"5702_CR1","doi-asserted-by":"publisher","first-page":"667","DOI":"10.1038\/s41591-019-0405-7","volume":"25","author":"AM Thomas","year":"2019","unstructured":"Thomas AM, et al. Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation. Nat Med. 2019;25(4):667\u201378. https:\/\/doi.org\/10.1038\/s41591-019-0405-7.","journal-title":"Nat Med"},{"issue":"4","key":"5702_CR2","doi-asserted-by":"publisher","first-page":"679","DOI":"10.1038\/s41591-019-0406-6","volume":"25","author":"J Wirbel","year":"2019","unstructured":"Wirbel J, et al. Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer. Nat Med. 2019;25(4):679\u201389. https:\/\/doi.org\/10.1038\/s41591-019-0406-6.","journal-title":"Nat Med"},{"issue":"6","key":"5702_CR3","doi-asserted-by":"publisher","first-page":"968","DOI":"10.1038\/s41591-019-0458-7","volume":"25","author":"S Yachida","year":"2019","unstructured":"Yachida S, Mizutani S, Shiroma H, et al. 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Direct involvement in the use of any animal or human data or tissue is not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"118"}}