Literature DB >> 33515241

wiSDOM: a visual and statistical analytics for interrogating microbiome.

Shih-Chi Su1,2,3, James E Galvin4, Shun-Fa Yang5,6, Wen-Hung Chung1,2, Lun-Ching Chang7.   

Abstract

MOTIVATION: We proposed a wiSDOM (web-based inclusionary analysis Suite for Disease-Oriented Metagenomics) R Shiny application which comprises six functional modules: (1) Initial visualization of sampling effort and distribution of dominant bacterial taxa among groups or individual samples at different taxonomic levels; (2) Statistical and visual analysis of α diversity; (3) Analysis of similarity (ANOSIM) of β diversity on UniFrac, Bray-Curtis, Horn-Morisita or Jaccard distance and visualizations; (4) Microbial biomarker discovery between two or more groups with various statistical and machine learning approaches; (5) Assessment of the clinical validity of selected biomarkers by creating the interactive receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC) for binary classifiers; and lastly (6) Functional prediction of metagenomes with PICRUSt or Tax4Fun.
RESULTS: The performance of wiSDOM has been evaluated in several of our previous studies for exploring microbial biomarkers and their clinical validity as well as assessing the alterations in bacterial diversity and functionality. The wiSDOM can be customized and visualized as per users' needs and specifications, allowing researchers without programming background to conduct comprehensive data mining and illustration using an intuitive browser-based interface.
AVAILABILITY AND IMPLEMENTATION: The browser-based R Shiny interface can be accessible via (https://lun-ching.shinyapps.io/wisdom/) and freely available at (https://github.com/lunching/wiSDOM). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) (2021). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Entities:  

Year:  2021        PMID: 33515241      PMCID: PMC8428577          DOI: 10.1093/bioinformatics/btab057

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  9 in total

1.  Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.

Authors:  Patrick D Schloss; Sarah L Westcott; Thomas Ryabin; Justine R Hall; Martin Hartmann; Emily B Hollister; Ryan A Lesniewski; Brian B Oakley; Donovan H Parks; Courtney J Robinson; Jason W Sahl; Blaz Stres; Gerhard G Thallinger; David J Van Horn; Carolyn F Weber
Journal:  Appl Environ Microbiol       Date:  2009-10-02       Impact factor: 4.792

2.  Integration of metagenomics-metabolomics reveals specific signatures and functions of airway microbiota in mite-sensitized childhood asthma.

Authors:  Chih-Yung Chiu; Hsin-Cheng Chou; Lun-Ching Chang; Wen-Lang Fan; Michael Cong Vinh Dinh; Yu-Lun Kuo; Wen-Hung Chung; Hsin-Chih Lai; Wen-Ping Hsieh; Shih-Chi Su
Journal:  Allergy       Date:  2020-07-13       Impact factor: 13.146

Review 3.  The human microbiome: at the interface of health and disease.

Authors:  Ilseung Cho; Martin J Blaser
Journal:  Nat Rev Genet       Date:  2012-03-13       Impact factor: 53.242

4.  DADA2: High-resolution sample inference from Illumina amplicon data.

Authors:  Benjamin J Callahan; Paul J McMurdie; Michael J Rosen; Andrew W Han; Amy Jo A Johnson; Susan P Holmes
Journal:  Nat Methods       Date:  2016-05-23       Impact factor: 28.547

5.  QIIME allows analysis of high-throughput community sequencing data.

Authors:  J Gregory Caporaso; Justin Kuczynski; Jesse Stombaugh; Kyle Bittinger; Frederic D Bushman; Elizabeth K Costello; Noah Fierer; Antonio Gonzalez Peña; Julia K Goodrich; Jeffrey I Gordon; Gavin A Huttley; Scott T Kelley; Dan Knights; Jeremy E Koenig; Ruth E Ley; Catherine A Lozupone; Daniel McDonald; Brian D Muegge; Meg Pirrung; Jens Reeder; Joel R Sevinsky; Peter J Turnbaugh; William A Walters; Jeremy Widmann; Tanya Yatsunenko; Jesse Zaneveld; Rob Knight
Journal:  Nat Methods       Date:  2010-04-11       Impact factor: 28.547

6.  Exact sequence variants should replace operational taxonomic units in marker-gene data analysis.

Authors:  Benjamin J Callahan; Paul J McMurdie; Susan P Holmes
Journal:  ISME J       Date:  2017-07-21       Impact factor: 10.302

7.  Integrative metagenomic and metabolomic analyses reveal severity-specific signatures of gut microbiota in chronic kidney disease.

Authors:  I-Wen Wu; Sheng-Siang Gao; Hsin-Cheng Chou; Huang-Yu Yang; Lun-Ching Chang; Yu-Lun Kuo; Michael Cong Vinh Dinh; Wen-Hung Chung; Chi-Wei Yang; Hsin-Chih Lai; Wen-Ping Hsieh; Shih-Chi Su
Journal:  Theranostics       Date:  2020-04-06       Impact factor: 11.556

8.  Gut Microbiota as Diagnostic Tools for Mirroring Disease Progression and Circulating Nephrotoxin Levels in Chronic Kidney Disease: Discovery and Validation Study.

Authors:  I-Wen Wu; Chan-Yu Lin; Lun-Ching Chang; Chin-Chan Lee; Chih-Yung Chiu; Heng-Jung Hsu; Chiao-Yin Sun; Yuen-Chan Chen; Yu-Lun Kuo; Chi-Wei Yang; Sheng-Siang Gao; Wen-Ping Hsieh; Wen-Hung Chung; Hsin-Chih Lai; Shih-Chi Su
Journal:  Int J Biol Sci       Date:  2020-01-01       Impact factor: 6.580

9.  Compositional and Functional Adaptations of Intestinal Microbiota and Related Metabolites in CKD Patients Receiving Dietary Protein Restriction.

Authors:  I-Wen Wu; Chin-Chan Lee; Heng-Jung Hsu; Chiao-Yin Sun; Yuen-Chan Chen; Kai-Jie Yang; Chi-Wei Yang; Wen-Hun Chung; Hsin-Chih Lai; Lun-Ching Chang; Shih-Chi Su
Journal:  Nutrients       Date:  2020-09-12       Impact factor: 5.717

  9 in total
  1 in total

1.  Namco: a microbiome explorer.

Authors:  Alexander Dietrich; Monica Steffi Matchado; Maximilian Zwiebel; Benjamin Ölke; Michael Lauber; Ilias Lagkouvardos; Jan Baumbach; Dirk Haller; Beate Brandl; Thomas Skurk; Hans Hauner; Sandra Reitmeier; Markus List
Journal:  Microb Genom       Date:  2022-08
  1 in total

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