Journal ArticleDOI
Using MicrobiomeAnalyst for comprehensive statistical, functional, and meta-analysis of microbiome data.
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TLDR
This protocol details MicrobiomeAnalyst, a user-friendly, web-based platform for comprehensive statistical, functional, and meta-analysis of microbiome data, a one-stop shop that enables microbiome researchers to thoroughly explore their preprocessed microbiome data via intuitive web interfaces.Abstract:
MicrobiomeAnalyst is an easy-to-use, web-based platform for comprehensive analysis of common data outputs generated from current microbiome studies. It enables researchers and clinicians with little or no bioinformatics training to explore a wide variety of well-established methods for microbiome data processing, statistical analysis, functional profiling and comparison with public datasets or known microbial signatures. MicrobiomeAnalyst currently contains four modules: Marker-gene Data Profiling (MDP), Shotgun Data Profiling (SDP), Projection with Public Data (PPD), and Taxon Set Enrichment Analysis (TSEA). This protocol will first introduce the MDP module by providing a step-wise description of how to prepare, process and normalize data; perform community profiling; identify important features; and conduct correlation and classification analysis. We will then demonstrate how to perform predictive functional profiling and introduce several unique features of the SDP module for functional analysis. The last two sections will describe the key steps involved in using the PPD and TSEA modules for meta-analysis and visual exploration of the results. In summary, MicrobiomeAnalyst offers a one-stop shop that enables microbiome researchers to thoroughly explore their preprocessed microbiome data via intuitive web interfaces. The complete protocol can be executed in ~70 min. This protocol details MicrobiomeAnalyst, a user-friendly, web-based platform for comprehensive statistical, functional, and meta-analysis of microbiome data.read more
Citations
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Using MetaboAnalyst 5.0 for LC–HRMS spectra processing, multi-omics integration and covariate adjustment of global metabolomics data
TL;DR: MetaboAnalyst 5.0 as discussed by the authors extends the previous 2011 Nature Protocol by providing stepwise instructions to optimize parameters for LC-HRMS spectra processing; obtain functional insights from peak list data; integrate metabolomics data with transcriptomics data or combine multiple metabolomics datasets; conduct exploratory statistical analysis with complex metadata.
Journal ArticleDOI
Applications of Machine Learning in Human Microbiome Studies: A Review on Feature Selection, Biomarker Identification, Disease Prediction and Treatment.
Laura Judith Marcos-Zambrano,Kanita Karaduzovic-Hadziabdic,Tatjana Loncar Turukalo,Piotr Przymus,Vladimir Trajkovik,Oliver Aasmets,Magali Berland,Aleksandra Gruca,Jasminka Hasic,Karel Hron,Thomas Klammsteiner,Mikhail Kolev,Leo Lahti,Marta B. Lopes,Victor Moreno,Irina Naskinova,Elin Org,Inês Paciência,Georgios Papoutsoglou,Rajesh Shigdel,Blaz Stres,Baiba Vilne,Malik Yousef,Eftim Zdravevski,Ioannis Tsamardinos,Enrique Carrillo de Santa Pau,Marcus J. Claesson,Isabel Moreno-Indias,Isabel Moreno-Indias,Jaak Truu +29 more
TL;DR: In this paper, a review of the state-of-the-art ML methods and respective software applied in human microbiome studies, performed as part of the COST Action ML4Microbiome activities, is presented.
Journal ArticleDOI
Tryptophan-derived microbial metabolites activate the aryl hydrocarbon receptor in tumor-associated macrophages to suppress anti-tumor immunity.
Kebria Hezaveh,Rahul S. Shinde,Andreas Klötgen,Marie Jo Halaby,S. Lamorte,M. Teresa Ciudad,Rene Quevedo,Luke Neufeld,Zhe Liu,Robbie Jin,Barbara Grünwald,Elisabeth G. Foerster,Danica Chaharlangi,Mengdi Guo,Priya Makhijani,Xin Zhang,Trevor J. Pugh,Devanand M. Pinto,Ileana L. Co,Alison P. McGuigan,Gun Ho Jang,Rama Khokha,Pamela S. Ohashi,Grainne M. O'Kane,Steven Gallinger,William Wiley Navarre,Heather Maughan,Dana J. Philpott,David J. Brooks,Tracy L. McGaha +29 more
TL;DR: In this article , the authors examined the impact of the aryl hydrocarbon receptor (AhR) in tumor-associated macrophage (TAM) function in pancreatic ductal adenocarcinoma (PDAC).
Journal ArticleDOI
Bile acids drive the newborn's gut microbiota maturation.
N. van Best,N. van Best,Ulrike Rolle-Kampczyk,Frank G. Schaap,Frank G. Schaap,Marijana Basic,S. W. M. Olde Damink,S. W. M. Olde Damink,André Bleich,Paul H. M. Savelkoul,M. von Bergen,M. von Bergen,John Penders,Mathias W. Hornef +13 more
TL;DR: The authors investigate the impact of the developing host hepatic metabolism on the murine intestinal microbiota composition with comparative analysis at immediate postnatal period, early infancy and weaning and adulthood.
Journal ArticleDOI
Mass spectrometry-based metabolomics in microbiome investigations.
Anelize Bauermeister,Helena Mannochio-Russo,Letícia V. Costa-Lotufo,Alan K. Jarmusch,Pieter C. Dorrestein,Pieter C. Dorrestein +5 more
TL;DR: In this article, the authors provide a foundational introduction to common forms of untargeted mass spectrometry and the types of data that can be obtained in the context of microbiome analysis.
References
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