The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Correlation detection strategies in microbial data sets vary widely in sensitivity and precision
Open accessAbstract
Disruption of healthy microbial communities has been linked to numerous diseases, yet microbial interactions are little understood. This is due in part to the large number of bacteria, and the much larger number of interactions (easily in the millions), making experimental investigation very difficult at best and necessitating the nascent field of computational exploration through microbial correlation networks. We benchmark the performance of eight correlation techniques on simulated and real data in response to challenges specific to microbiome studies: fractional sampling of ribosomal RNA sequences, uneven sampling depths, rare microbes and a high proportion of zero counts. Also tested is the ability to distinguish signals from noise, and detect a range of ecological and time-series relationships. Finally, we provide specific recommendations for correlation technique usage. Although some methods perform better than others, there is still considerable need for improvement in current techniques.
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Cites
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Cited by
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Metadata
- Authors
- Weiss, S., Van Treuren, W., Lozupone, C., Faust, K., Friedman, J., Deng, Y., Xia, L. C., Xu, Z. Z., Ursell, L., Alm, E. J., Birmingham, A., Cram, J. A., Fuhrman, J. A., Raes, J., Sun, F., Zhou, J., & Knight, R.
- Venue
- The ISME Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-02-23
- Volume
- 10
- Issue
- 7
- Pages
- 1669-1681
- ISSN
- 1751-7362 (ISSN-L)
- 1751-7370
- OpenAlex
- W2280650020
- Cited by
- 861
- References
- 12
- FWCI
- 30.85
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Weiss, S., Van Treuren, W., Lozupone, C., Faust, K., Friedman, J., Deng, Y., Xia, L. C., Xu, Z. Z., Ursell, L., Alm, E. J., Birmingham, A., Cram, J. A., Fuhrman, J. A., Raes, J., Sun, F., Zhou, J., & Knight, R. (2016). Correlation detection strategies in microbial data sets vary widely in sensitivity and precision. The ISME Journal. https://doi.org/10.1038/ismej.2015.235
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