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Compositional zero-inflated network estimation for microbiome data.

BMC bioinformatics

Ha MJ, Kim J, Galloway-Peña J, Do KA, Peterson CB.
PMID: 33371887
BMC Bioinformatics. 2020 Dec 28;21:581. doi: 10.1186/s12859-020-03911-w.

BACKGROUND: The estimation of microbial networks can provide important insight into the ecological relationships among the organisms that comprise the microbiome. However, there are a number of critical statistical challenges in the inference of such networks from high-throughput data....

Cite
Ha MJ, Kim J, Galloway-Peña J, et al. Compositional zero-inflated network estimation for microbiome data. BMC Bioinformatics. 2020;21:581doi: 10.1186/s12859-020-03911-w.
Ha, M. J., Kim, J., Galloway-Peña, J., Do, K. A., & Peterson, C. B. (2020). Compositional zero-inflated network estimation for microbiome data. BMC bioinformatics, 21581. https://doi.org/10.1186/s12859-020-03911-w
Ha, Min Jin, et al. "Compositional zero-inflated network estimation for microbiome data." BMC bioinformatics vol. 21 (2020): 581. doi: https://doi.org/10.1186/s12859-020-03911-w
Ha MJ, Kim J, Galloway-Peña J, Do KA, Peterson CB. Compositional zero-inflated network estimation for microbiome data. BMC Bioinformatics. 2020 Dec 28;21:581. doi: 10.1186/s12859-020-03911-w. PMID: 33371887; PMCID: PMC7768662.
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