KombOver: Efficient k-core and K-truss based characterization of perturbations within the human gut microbiome
KombOver: Efficient k-core and K-truss based characterization of perturbations within the human gut microbiome
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KombOver：基于高效 k 核和 K 桁架的人类肠道微生物组扰动表征
DOI：
10.1142/9789811286421_0039
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Treangen, Todd J.
中科院分区：
文献类型：
--
作者：
Sapoval, Nicolae;Tanevski, Marko;Treangen, Todd J.
存在于人类胃肠道中的微生物通常与人类健康和疾病结果有关。由于近年来技术和方法的进步，宏基因组测序数据和旨在分析宏基因组数据的计算方法有助于提高对人类肠道微生物组与疾病之间联系的理解。然而，虽然最近已经开发了许多方法来从宿主相关的微生物组数据中提取定量和定性结果，但仍然需要改进的计算工具来用短读段测序数据跟踪微生物组动态。以前，我们已经提出KOMB作为一种从头工具，用于识别宏基因组中的拷贝数变异，以表征微生物基因组动态响应扰动。在这项工作中，我们提出了KombOver（KO），其中包括与我们以前的工作有关的四个关键贡献：（i）它扩展到大型微生物组研究群组，（ii）它包括基于k-核心和K-桁架的分析，（iii）我们提供了对各种基于图的宏基因组表示之间的关系的理论理解的基础，以及（iv）我们提供了改进的用户体验，其中包含运行代码和更具描述性的输出/结果。为了突出上述优势，我们将KO应用于近1000个人体微生物组样本，每个样本需要不到10分钟和10 GB RAM来处理这些数据。此外，我们强调了如何基于图形的方法，如k-核心和K-桁架可以提供信息，以查明肌痛性脑脊髓炎/慢性疲劳综合征（ME/CFS）队列内的微生物群落动态。KO是开源的，可在以下网址下载/使用：https://github.com/treangenlab/komb
The microbes present in the human gastrointestinal tract are regularly linked to human health and disease outcomes. Thanks to technological and methodological advances in recent years, metagenomic sequencing data, and computational methods designed to analyze metagenomic data, have contributed to improved understanding of the link between the human gut microbiome and disease. However, while numerous methods have been recently developed to extract quantitative and qualitative results from host-associated microbiome data, improved computational tools are still needed to track microbiome dynamics with short-read sequencing data. Previously we have proposed KOMB as a de novo tool for identifying copy number variations in metagenomes for characterizing microbial genome dynamics in response to perturbations. In this work, we present KombOver (KO), which includes four key contributions with respect to our previous work: (i) it scales to large microbiome study cohorts, (ii) it includes both k-core and K-truss based analysis, (iii) we provide the foundation of a theoretical understanding of the relation between various graph-based metagenome representations, and (iv) we provide an improved user experience with easier-to-run code and more descriptive outputs/results. To highlight the aforementioned benefits, we applied KO to nearly 1000 human microbiome samples, requiring less than 10 minutes and 10 GB RAM per sample to process these data. Furthermore, we highlight how graph-based approaches such as k-core and K-truss can be informative for pinpointing microbial community dynamics within a myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) cohort. KO is open source and available for download/use at: https://github.com/treangenlab/komb
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DOI：
10.1093/bioinformatics/btab309
发表时间：
2021-07-12
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Khan J;Patro R
通讯作者：
Patro R
组装图上的宏基因组应变解析
DOI：
10.1101/2020.09.06.284828
发表时间：
2020
期刊：
bioRxiv
影响因子：
--
作者：
C. Quince;S. Nurk;S. Raguideau;Robert S James;Orkun S. Soyer;J. Summers;A. Limasset;A. M. Eren;R. Chikhi;A. E. Darling
通讯作者：
A. E. Darling
影响因子：
64.8
作者：
Lloyd-Price, Jason;Arze, Cesar;Yajnik, Vijay
通讯作者：
Yajnik, Vijay
影响因子：
48
作者：
Curry, Kristen D.;Wang, Qi;Nute, Michael G.;Tyshaieva, Alona;Reeves, Elizabeth;Soriano, Sirena;Wu, Qinglong;Graeber, Enid;Finzer, Patrick;Mendling, Werner;Savidge, Tor;Villapol, Sonia;Dilthey, Alexander;Treangen, Todd J.
通讯作者：
Treangen, Todd J.
影响因子：
64.8
作者：
Jarvis, Erich D;Formenti, Giulio;Rhie, Arang;Guarracino, Andrea;Yang, Chentao;Wood, Jonathan;Tracey, Alan;Thibaud-Nissen, Francoise;Vollger, Mitchell R;Porubsky, David;Cheng, Haoyu;Asri, Mobin;Logsdon, Glennis A;Carnevali, Paolo;Chaisson, Mark J P;Chin, Chen-Shan;Cody, Sarah;Collins, Joanna;Ebert, Peter;Escalona, Merly;Fedrigo, Olivier;Fulton, Robert S;Fulton, Lucinda L;Garg, Shilpa;Gerton, Jennifer L;Ghurye, Jay;Granat, Anastasiya;Green, Richard E;Harvey, William;Hasenfeld, Patrick;Hastie, Alex;Haukness, Marina;Jaeger, Erich B;Jain, Miten;Kirsche, Melanie;Kolmogorov, Mikhail;Korbel, Jan O;Koren, Sergey;Korlach, Jonas;Lee, Joyce;Li, Daofeng;Lindsay, Tina;Lucas, Julian;Luo, Feng;Marschall, Tobias;Mitchell, Matthew W;McDaniel, Jennifer;Nie, Fan;Olsen, Hugh E;Olson, Nathan D;Pesout, Trevor;Potapova, Tamara;Puiu, Daniela;Regier, Allison;Ruan, Jue;Salzberg, Steven L;Sanders, Ashley D;Schatz, Michael C;Schmitt, Anthony;Schneider, Valerie A;Selvaraj, Siddarth;Shafin, Kishwar;Shumate, Alaina;Stitziel, Nathan O;Stober, Catherine;Torrance, James;Wagner, Justin;Wang, Jianxin;Wenger, Aaron;Xiao, Chuanle;Zimin, Aleksey V;Zhang, Guojie;Wang, Ting;Li, Heng;Garrison, Erik;Haussler, David;Hall, Ira;Zook, Justin M;Eichler, Evan E;Phillippy, Adam M;Paten, Benedict;Howe, Kerstin;Miga, Karen H
通讯作者：
Miga, Karen H