The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
MicrobiomeAnalyst: a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data
Open accessAbstract
The widespread application of next-generation sequencing technologies has revolutionized microbiome research by enabling high-throughput profiling of the genetic contents of microbial communities. How to analyze the resulting large complex datasets remains a key challenge in current microbiome studies. Over the past decade, powerful computational pipelines and robust protocols have been established to enable efficient raw data processing and annotation. The focus has shifted toward downstream statistical analysis and functional interpretation. Here, we introduce MicrobiomeAnalyst, a user-friendly tool that integrates recent progress in statistics and visualization techniques, coupled with novel knowledge bases, to enable comprehensive analysis of common data outputs produced from microbiome studies. MicrobiomeAnalyst contains four modules - the Marker Data Profiling module offers various options for community profiling, comparative analysis and functional prediction based on 16S rRNA marker gene data; the Shotgun Data Profiling module supports exploratory data analysis, functional profiling and metabolic network visualization of shotgun metagenomics or metatranscriptomics data; the Taxon Set Enrichment Analysis module helps interpret taxonomic signatures via enrichment analysis against >300 taxon sets manually curated from literature and public databases; finally, the Projection with Public Data module allows users to visually explore their data with a public reference data for pattern discovery and biological insights. MicrobiomeAnalyst is freely available at http://www.microbiomeanalyst.ca.
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Cites
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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
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QIIME allows analysis of high-throughput community sequencing data
Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., Fierer, N., Peña, A. G., Goodrich, J. K., Gordon, J. I., et al. (2010) · Nature Methods · doi:10.1038/nmeth.f.303 · Cited by 34,887
Structure, function and diversity of the healthy human microbiome
The Human Microbiome Project Consortium (2012) · Nature · doi:10.1038/nature11234 · Cited by 11,726
A human gut microbial gene catalogue established by metagenomic sequencing
MetaHIT Consortium, Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, K. S., Manichanh, C., Nielsen, T., Pons, N., Levenez, F., et al. (2010) · Nature · doi:10.1038/nature08821 · Cited by 11,624
Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences
Langille, M. G. I., Zaneveld, J., Caporaso, J. G., McDonald, D., Knights, D., Reyes, J. A., Clemente, J. C., Burkepile, D. E., Vega Thurber, R. L., Knight, R., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2676 · Cited by 9,116
The Effect of Diet on the Human Gut Microbiome: A Metagenomic Analysis in Humanized Gnotobiotic Mice
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“As shown in Figure 2B, the abundance of Bacteroidetes phylum was lower, while the abundance of Firmicutes and Proteobacteria phyla were both higher, in mice consuming the WSD as compared to the LFD, an expected effect of the WSD on the gut microbiota (35).”
ResultEnrichment Map: A Network-Based Method for Gene-Set Enrichment Visualization and Interpretation
Merico, D., Isserlin, R., Stueker, O., Emili, A., & Bader, G. D. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013984 · Cited by 2,235
Persistent gut microbiota immaturity in malnourished Bangladeshi children
Subramanian, S., Huq, S., Yatsunenko, T., Haque, R., Mahfuz, M., Alam, M. A., Benezra, A., DeStefano, J., Meier, M. F., Muegge, B. D., et al. (2014) · Nature · doi:10.1038/nature13421 · Cited by 1,270
Looking for a Signal in the Noise: Revisiting Obesity and the Microbiome
Sze, M. A., & Schloss, P. D. (2016) · mBio · doi:10.1128/mbio.01018-16 · Cited by 600 · cited 2×
“In future releases, we intend to further enhance the support for more rigorous statistical meta-analysis (19,46).”
Background
Cited by
Culturing the human microbiota and culturomics
Lagier, J.-C., Dubourg, G., Million, M., Cadoret, F., Bilen, M., Fenollar, F., Levasseur, A., Rolain, J.-M., Fournier, P.-E., & Raoult, D. (2018) · Nature Reviews Microbiology · doi:10.1038/s41579-018-0041-0 · Cited by 872
Hezaveh, K., Shinde, R. S., Klötgen, A., Halaby, M. J., Lamorte, S., Ciudad, M. T., Quevedo, R., Neufeld, L., Liu, Z. Q., Jin, R., et al. (2022) · Immunity · doi:10.1016/j.immuni.2022.01.006 · Cited by 746
Lu, Y., Zhou, G., Ewald, J., Pang, Z., Shiri, T., & Xia, J. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad407 · Cited by 623
Self-citationCurrent challenges and best-practice protocols for microbiome analysis
Bharti, R., & Grimm, D. G. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbz155 · Cited by 592
microbiomeMarker: an R/Bioconductor package for microbiome marker identification and visualization
Cao, Y., Dong, Q., Wang, D., Zhang, P., Liu, Y., & Niu, C. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac438 · Cited by 438
Metadata
- Authors
- Dhariwal, A., Chong, J., Habib, S., King, I. L., Agellon, L. B., & Xia, J.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-04-26
- Volume
- 45
- Issue
- W1
- Pages
- W180-W188
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2608515760
- Cited by
- 1,885
- References
- 10
- FWCI
- 8.76
- Type
- journal article
- Language
- en
- Open access
- gold
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- Dhariwal, A., Chong, J., Habib, S., King, I. L., Agellon, L. B., & Xia, J. (2017). MicrobiomeAnalyst: a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data. Nucleic Acids Research. https://doi.org/10.1093/nar/gkx295
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