The Statistical Analysis of Compositional Data

The Microbiota-Gut-Brain Axis

Cryan, J. F., O'Riordan, K. J., Cowan, C. S. M., Sandhu, K. V., Bastiaanssen, T. F. S., Boehme, M., Codagnone, M. G., Cussotto, S., Fulling, C., Golubeva, A. V., et al. (2019) · Physiological Reviews · doi:10.1152/physrev.00018.2018 · Cited by 5,286 · see citing works

Microbiome Datasets Are Compositional: And This Is Not Optional

Gloor, G. B., Macklaim, J. M., Pawlowsky-Glahn, V., & Egozcue, J. J. (2017) · Frontiers in Microbiology · doi:10.3389/fmicb.2017.02224 · Cited by 3,044 · see citing works

US Health Care Spending by Payer and Health Condition, 1996-2016

Dieleman, J. L., Cao, J., Chapin, A., Chen, C., Li, Z., Liu, A., Horst, C., Kaldjian, A., Matyasz, T., Scott, K. W., et al. (2020) · JAMA · doi:10.1001/jama.2020.0734 · Cited by 1,313 · see citing works

Unifying the analysis of high-throughput sequencing datasets: characterizing RNA-seq, 16S rRNA gene sequencing and selective growth experiments by compositional data analysis

Fernandes, A. D., Reid, J. N., Macklaim, J. M., McMurrough, T. A., Edgell, D. R., & Gloor, G. B. (2014) · Microbiome · doi:10.1186/2049-2618-2-15 · Cited by 1,329 · see citing works

Combined Effects of Time Spent in Physical Activity, Sedentary Behaviors and Sleep on Obesity and Cardio-Metabolic Health Markers: A Novel Compositional Data Analysis Approach

Chastin, S. F. M., Palarea-Albaladejo, J., Dontje, M. L., & Skelton, D. A. (2015) · PLOS ONE · doi:10.1371/journal.pone.0139984 · Cited by 1,034 · see citing works

Sex Differences in Brain Gray and White Matter in Healthy Young Adults: Correlations with Cognitive Performance

Gur, R. C., Turetsky, B. I., Matsui, M., Yan, M., Bilker, W., Hughett, P., & Gur, R. E. (1999) · The Journal of Neuroscience · doi:10.1523/jneurosci.19-10-04065.1999 · Cited by 909 · see citing works

The Microbiota of Breast Tissue and Its Association with Breast Cancer

Urbaniak, C., Gloor, G. B., Brackstone, M., Scott, L., Tangney, M., & Reid, G. (2016) · Applied and Environmental Microbiology · doi:10.1128/aem.01235-16 · Cited by 625 · see citing works

A Taxonomic Signature of Obesity in the Microbiome? Getting to the Guts of the Matter

Finucane, M. M., Sharpton, T. J., Laurent, T. J., & Pollard, K. S. (2014) · PLoS ONE · doi:10.1371/journal.pone.0084689 · Cited by 321 · see citing works

Endometrial microbiota composition is associated with reproductive outcome in infertile patients

Moreno, I., Garcia-Grau, I., Perez-Villaroya, D., Gonzalez-Monfort, M., Bahçeci, M., Barrionuevo, M. J., Taguchi, S., Puente, E., Dimattina, M., Lim, M. W., et al. (2022) · Microbiome · doi:10.1186/s40168-021-01184-w · Cited by 325 · see citing works

Native American gene flow into Polynesia predating Easter Island settlement

Ioannidis, A. G., Blanco-Portillo, J., Sandoval, K., Hagelberg, E., Miquel-Poblete, J. F., Moreno-Mayar, J. V., Rodríguez-Rodríguez, J. E., Quinto-Cortés, C. D., Auckland, K., Parks, T., et al. (2020) · Nature · doi:10.1038/s41586-020-2487-2 · Cited by 196 · see citing works

Systems protobiology: origin of life in lipid catalytic networks

Lancet, D., Zidovetzki, R., & Markovitch, O. (2018) · Journal of The Royal Society Interface · doi:10.1098/rsif.2018.0159 · Cited by 182 · see citing works

Quantifying the influence of biochar on the physical and hydrological properties of dissimilar soils

Peake, L. R., Reid, B. J., & Tang, X. (2014) · Geoderma · doi:10.1016/j.geoderma.2014.07.002 · Cited by 182 · see citing works

Hierarchical coding for sequential task events in the monkey prefrontal cortex

Sigala, N., Kusunoki, M., Nimmo-Smith, I., Gaffan, D., & Duncan, J. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0802569105 · Cited by 140 · see citing works

Experimental and computational framework for a dynamic protein atlas of human cell division

Cai, Y., Hossain, M. J., Hériché, J.-K., Politi, A. Z., Walther, N., Koch, B., Wachsmuth, M., Nijmeijer, B., Kueblbeck, M., Martinic-Kavur, M., et al. (2018) · Nature · doi:10.1038/s41586-018-0518-z · Cited by 121 · see citing works

MTOR signaling orchestrates stress-induced mutagenesis, facilitating adaptive evolution in cancer

Cipponi, A., Goode, D. L., Bedo, J., McCabe, M. J., Pajic, M., Croucher, D. R., Rajal, A. G., Junankar, S. R., Saunders, D. N., Lobachevsky, P., et al. (2020) · Science · doi:10.1126/science.aau8768 · Cited by 103 · see citing works

Benchmarking microbiome transformations favors experimental quantitative approaches to address compositionality and sampling depth biases

Lloréns-Rico, V., Vieira-Silva, S., Gonçalves, P. J., Falony, G., & Raes, J. (2021) · Nature Communications · doi:10.1038/s41467-021-23821-6 · Cited by 73 · see citing works

Sedimentary chemofacies characterization by means of multivariate analysis

Montero-Serrano, J. C., Palarea-Albaladejo, J., Martín-Fernández, J. A., Martínez-Santana, M., & Gutiérrez-Martín, J. V. (2010) · Sedimentary Geology · doi:10.1016/j.sedgeo.2010.04.013 · Cited by 64 · see citing works

Library Preparation and Sequencing Platform Introduce Bias in Metagenomic-Based Characterizations of Microbiomes

Poulsen, C. S., Ekstrøm, C. T., Aarestrup, F. M., & Pamp, S. J. (2022) · Microbiology Spectrum · doi:10.1128/spectrum.00090-22 · Cited by 50 · see citing works

On the Compositional Analysis of Fatty Acids in Pork

Ros-Freixedes, R., & Estany, J. (2014) · Journal of Agricultural Biological and Environmental Statistics · doi:10.1007/s13253-013-0162-x · Cited by 46 · see citing works

Multiomics Implicate Gut Microbiota in Altered Lipid and Energy Metabolism in Parkinson’s Disease

Pereira, P. A. B., Trivedi, D. K., Silverman, J., Duru, I. C., Paulin, L., Auvinen, P., & Scheperjans, F. (2022) · npj Parkinson s Disease · doi:10.1038/s41531-022-00300-3 · Cited by 40 · see citing works

Desiccation tolerance in <i>Anopheles coluzzii</i>: the effects of spiracle size and cuticular hydrocarbons

Arcaz, A. C., Huestis, D. L., Dao, A., Yaro, A. S., Diallo, M., Andersen, J., Blomquist, G. J., & Lehmann, T. (2016) · Journal of Experimental Biology · doi:10.1242/jeb.135665 · Cited by 40 · see citing works

Transformation, normalization, and batch effect in the analysis of mass spectrometry data for omics studies,

Mertens, B. J. A. (2017) · Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry · doi:10.1007/978-3-319-45809-0_1 · Cited by 30 · see citing works

A Fast, Easy, and Efficient Estimator for Multiparty Electoral Data

Honaker, J., Katz, J. N., & King, G. (2002) · Political Analysis · doi:10.1093/pan/10.1.84 · Cited by 5 · see citing works