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Generalized Linear Models With Linear Constraints for Microbiome Compositional Data

Publication ,  Journal Article
Lu, J; Shi, P; Li, H
Published in: Biometrics
March 1, 2019

Motivated by regression analysis for microbiome compositional data, this article considers generalized linear regression analysis with compositional covariates, where a group of linear constraints on regression coefficients are imposed to account for the compositional nature of the data and to achieve subcompositional coherence. A penalized likelihood estimation procedure using a generalized accelerated proximal gradient method is developed to efficiently estimate the regression coefficients. A de-biased procedure is developed to obtain asymptotically unbiased and normally distributed estimates, which leads to valid confidence intervals of the regression coefficients. Simulations results show the correctness of the coverage probability of the confidence intervals and smaller variances of the estimates when the appropriate linear constraints are imposed. The methods are illustrated by a microbiome study in order to identify bacterial species that are associated with inflammatory bowel disease (IBD) and to predict IBD using fecal microbiome.

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Published In

Biometrics

DOI

EISSN

1541-0420

ISSN

0006-341X

Publication Date

March 1, 2019

Volume

75

Issue

1

Start / End Page

235 / 244

Publisher

Oxford University Press (OUP)

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 0199 Other Mathematical Sciences
  • 0104 Statistics
 

Citation

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Lu, J., Shi, P., & Li, H. (2019). Generalized Linear Models With Linear Constraints for Microbiome Compositional Data. Biometrics, 75(1), 235–244. https://doi.org/10.1111/biom.12956
Lu, Jiarui, Pixu Shi, and Hongzhe Li. “Generalized Linear Models With Linear Constraints for Microbiome Compositional Data.” Biometrics 75, no. 1 (March 1, 2019): 235–44. https://doi.org/10.1111/biom.12956.
Lu J, Shi P, Li H. Generalized Linear Models With Linear Constraints for Microbiome Compositional Data. Biometrics. 2019 Mar 1;75(1):235–44.
Lu, Jiarui, et al. “Generalized Linear Models With Linear Constraints for Microbiome Compositional Data.” Biometrics, vol. 75, no. 1, Oxford University Press (OUP), Mar. 2019, pp. 235–44. Crossref, doi:10.1111/biom.12956.
Lu J, Shi P, Li H. Generalized Linear Models With Linear Constraints for Microbiome Compositional Data. Biometrics. Oxford University Press (OUP); 2019 Mar 1;75(1):235–244.
Journal cover image

Published In

Biometrics

DOI

EISSN

1541-0420

ISSN

0006-341X

Publication Date

March 1, 2019

Volume

75

Issue

1

Start / End Page

235 / 244

Publisher

Oxford University Press (OUP)

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 0199 Other Mathematical Sciences
  • 0104 Statistics