Compositional zero-inflated network estimation for microbiome data
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Junghi Kim | Kim-Anh Do | Christine B. Peterson | Christine B. Peterson | Min Jin Ha | Jessica Galloway-Peña | K. Do | C. Peterson | Junghi Kim | M. Ha | J. Galloway-Peña
[1] Christian L. Müller,et al. Microbial Networks in SPRING - Semi-parametric Rank-Based Correlation and Partial Correlation Estimation for Quantitative Microbiome Data , 2019, bioRxiv.
[2] Ali Shojaie,et al. Selection and estimation for mixed graphical models. , 2013, Biometrika.
[3] M. Newman,et al. Mixing patterns in networks. , 2002, Physical review. E, Statistical, nonlinear, and soft matter physics.
[4] E. Le Chatelier,et al. Gut microbiome modulates response to anti–PD-1 immunotherapy in melanoma patients , 2018, Science.
[5] Andrew McDavid,et al. GRAPHICAL MODELS FOR ZERO-INFLATED SINGLE CELL GENE EXPRESSION. , 2016, The annals of applied statistics.
[6] N. Meinshausen,et al. High-dimensional graphs and variable selection with the Lasso , 2006, math/0608017.
[7] Gerard Muyzer,et al. A comparison of taxon co-occurrence patterns for macro- and microorganisms. , 2007, Ecology.
[8] S. Mazmanian,et al. The gut microbiota shapes intestinal immune responses during health and disease , 2009, Nature Reviews Immunology.
[9] Michael I. Jordan. Graphical Models , 1998 .
[10] Wei Lin,et al. Large Covariance Estimation for Compositional Data Via Composition-Adjusted Thresholding , 2016, Journal of the American Statistical Association.
[11] J. Goedert,et al. Human gut microbiome and risk for colorectal cancer. , 2013, Journal of the National Cancer Institute.
[12] Hubert Rehrauer,et al. A global network of coexisting microbes from environmental and whole-genome sequence data. , 2010, Genome research.
[13] Christine B. Peterson,et al. Gut Microbiome Signatures are Predictive of Infectious Risk Following Induction Therapy for Acute Myeloid Leukemia. , 2019, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.
[14] Pradeep Ravikumar,et al. Graphical models via univariate exponential family distributions , 2013, J. Mach. Learn. Res..
[15] S. Turroni,et al. The Same Microbiota and a Potentially Discriminant Metabolome in the Saliva of Omnivore, Ovo-Lacto-Vegetarian and Vegan Individuals , 2014, PloS one.
[16] R. Tibshirani,et al. Sparse inverse covariance estimation with the graphical lasso. , 2008, Biostatistics.
[17] Lingling An,et al. Investigating microbial co-occurrence patterns based on metagenomic compositional data , 2015, Bioinform..
[18] Christian L. Müller,et al. Sparse and Compositionally Robust Inference of Microbial Ecological Networks , 2014, PLoS Comput. Biol..
[19] Yuqing Yang,et al. Inference of Environmental Factor-Microbe and Microbe-Microbe Associations from Metagenomic Data Using a Hierarchical Bayesian Statistical Model. , 2017, Cell systems.
[20] Chenping Zhang,et al. Variations in oral microbiota associated with oral cancer , 2017, Scientific Reports.
[21] Michael I. Jordan,et al. Graphical Models, Exponential Families, and Variational Inference , 2008, Found. Trends Mach. Learn..
[22] John Aitchison,et al. The Statistical Analysis of Compositional Data , 1986 .
[23] HUAYING FANG,et al. gCoda: Conditional Dependence Network Inference for Compositional Data , 2017, J. Comput. Biol..
[24] Arthur Kaser,et al. Gut microbiome, obesity, and metabolic dysfunction. , 2011, The Journal of clinical investigation.
[25] LambertDiane. Zero-inflated Poisson regression, with an application to defects in manufacturing , 1992 .
[26] Jonathan Friedman,et al. Inferring Correlation Networks from Genomic Survey Data , 2012, PLoS Comput. Biol..
[27] C. Schadt,et al. Linking Associations of Rare Low-Abundance Species to Their Environments by Association Networks , 2018, Front. Microbiol..
[28] E. Borenstein,et al. Patterns of salivary microbiota injury and oral mucositis in recipients of allogeneic hematopoietic stem cell transplantation. , 2020, Blood advances.
[29] Hongyu Zhao,et al. CCLasso: correlation inference for compositional data through Lasso , 2015, Bioinform..
[30] Natalia N. Ivanova,et al. Symbiosis insights through metagenomic analysis of a microbial consortium. , 2006, Nature Reviews Microbiology.
[31] Pradeep Ravikumar,et al. Mixed Graphical Models via Exponential Families , 2014, AISTATS.
[32] Jizhong Zhou,et al. Preliminary analysis of salivary microbiome and their potential roles in oral lichen planus , 2016, Scientific Reports.
[33] Tianxi Li,et al. High-Dimensional Mixed Graphical Models , 2013, 1304.2810.
[34] J. Aitchison. A new approach to null correlations of proportions , 1981 .
[35] Albert,et al. Emergence of scaling in random networks , 1999, Science.
[36] K. Peck,et al. Bloodstream infections in adult patients with cancer: clinical features and pathogenic significance of Staphylococcus aureus bacteremia , 2012, Supportive Care in Cancer.
[37] Curtis Huttenhower,et al. Microbial Co-occurrence Relationships in the Human Microbiome , 2012, PLoS Comput. Biol..
[38] Blair J. Rossetti,et al. Biogeography of a human oral microbiome at the micron scale , 2016, Proceedings of the National Academy of Sciences.
[39] R. Jenq,et al. Intestinal microbiota-related effects on graft-versus-host disease , 2015, International Journal of Hematology.
[40] M. Brennan,et al. Lasting Gammaproteobacteria profile changes characterized hematological cancer patients who developed oral mucositis following conditioning therapy , 2020, Journal of oral microbiology.
[41] James Versalovic,et al. Human microbiome in health and disease. , 2012, Annual review of pathology.
[42] A. Salner,et al. Integrated Analysis of Clinical and Microbiome Risk Factors Associated with the Development of Oral Candidiasis during Cancer Chemotherapy , 2019, Journal of fungi.
[43] A. Kostic,et al. The microbiome in inflammatory bowel disease: current status and the future ahead. , 2014, Gastroenterology.