메뉴 건너뛰기




Volumn 2, Issue 1, 2017, Pages

Balance trees reveal microbial niche differentiation

Author keywords

Aitchison geometry; Balance trees; Compositionality; Cystic fibrosis; Niche; Soil microbiology

Indexed keywords


EID: 85034058140     PISSN: None     EISSN: 23795077     Source Type: Journal    
DOI: 10.1128/mSystems.00162-16     Document Type: Article
Times cited : (213)

References (27)
  • 2
    • 3342920241 scopus 로고    scopus 로고
    • Microbial acidification and pH effects on trace element release from sewage sludge
    • Qureshi S, Richards BK, Steenhuis TS, McBride MB, Baveye P, Dousset S. 2004. Microbial acidification and pH effects on trace element release from sewage sludge. Environ Pollut 132:61-71. https://doi.org/10.1016/j.envpol.2004.03.024.
    • (2004) Environ Pollut , vol.132 , pp. 61-71
    • Qureshi, S.1    Richards, B.K.2    Steenhuis, T.S.3    McBride, M.B.4    Baveye, P.5    Dousset, S.6
  • 3
    • 84975717775 scopus 로고    scopus 로고
    • It's all relative: Analyzing microbiome data as compositions
    • Gloor GB, Wu JR, Pawlowsky-Glahn V, Egozcue JJ. 2016. It's all relative: analyzing microbiome data as compositions. Ann Epidemiol 26:322-329. https://doi.org/10.1016/j.annepidem.2016.03.003.
    • (2016) Ann Epidemiol , vol.26 , pp. 322-329
    • Gloor, G.B.1    Wu, J.R.2    Pawlowsky-Glahn, V.3    Egozcue, J.J.4
  • 4
    • 84996599775 scopus 로고    scopus 로고
    • Compositional data analysis of the Microbiome: Fundamentals, tools, and challenges
    • Tsilimigras MCB, Fodor AA. 2016. Compositional data analysis of the Microbiome: fundamentals, tools, and challenges. Ann Epidemiol 26: 330-335. https://doi.org/10.1016/j.annepidem.2016.03.002.
    • (2016) Ann Epidemiol , vol.26 , pp. 330-335
    • Tsilimigras, M.C.B.1    Fodor, A.A.2
  • 5
    • 84866925227 scopus 로고    scopus 로고
    • Caution! Compositions! Can constraints on omics data lead analyses astray?
    • Lovell D, Muller W, Taylor J, Zwart A, Helliwell C. 2010. Caution! Compositions! Can constraints on omics data lead analyses astray? CSIRO 1-44.
    • (2010) CSIRO , pp. 1-44
    • Lovell, D.1    Muller, W.2    Taylor, J.3    Zwart, A.4    Helliwell, C.5
  • 6
    • 84865733148 scopus 로고    scopus 로고
    • Inferring correlation networks from genomic survey data
    • Friedman J, Alm EJ. 2012. Inferring correlation networks from genomic survey data. PLoS Comput Biol 8:e1002687. https://doi.org/10.1371/journal.pcbi.1002687.
    • (2012) PLoS Comput Biol , vol.8 , pp. e1002687
    • Friedman, J.1    Alm, E.J.2
  • 7
    • 84926322943 scopus 로고    scopus 로고
    • Proportionality: A valid alternative to correlation for relative data
    • Lovell D, Pawlowsky-Glahn V, Egozcue JJ, Marguerat S, Bähler J. 2015. Proportionality: a valid alternative to correlation for relative data. PLoS Comput Biol 11:e1004075. https://doi.org/10.1371/journal.pcbi.1004075.
    • (2015) PLoS Comput Biol , vol.11 , pp. e1004075
    • Lovell, D.1    Pawlowsky-Glahn, V.2    Egozcue, J.J.3    Marguerat, S.4    Bähler, J.5
  • 8
    • 84930608352 scopus 로고    scopus 로고
    • Sparse and compositionally robust inference of microbial ecological networks
    • Kurtz ZD, Müller CL, Miraldi ER, Littman DR. 2015. Sparse and compositionally robust inference of microbial ecological networks. PLoS Comput Biol 11:e1004226. https://doi.org/10.1371/journal.pcbi.1004226.
    • (2015) PLoS Comput Biol , vol.11 , pp. e1004226
    • Kurtz, Z.D.1    Müller, C.L.2    Miraldi, E.R.3    Littman, D.R.4
  • 10
    • 84863920287 scopus 로고    scopus 로고
    • Microbial interactions: From networks to models
    • Faust K, Raes J. 2012. Microbial interactions: from networks to models. Nat Rev Microbiol 10:538-550. https://doi.org/10.1038/nrmicro2832.
    • (2012) Nat Rev Microbiol , vol.10 , pp. 538-550
    • Faust, K.1    Raes, J.2
  • 11
    • 85041666248 scopus 로고    scopus 로고
    • Robust methods for differential abundance analysis in marker gene surveys
    • Paulson JN, Stine OC, Bravo HC, Pop M. 2016. Robust methods for differential abundance analysis in marker gene surveys. Nat Methods 116:1477-1490.
    • (2016) Nat Methods , vol.116 , pp. 1477-1490
    • Paulson, J.N.1    Stine, O.C.2    Bravo, H.C.3    Pop, M.4
  • 12
    • 84946878517 scopus 로고    scopus 로고
    • Analysis of composition of microbiomes: A novel method for studying microbial composition
    • Mandal S, Van Treuren W, White RA, Eggesbø M, Knight R, Peddada SD. 2015. Analysis of composition of microbiomes: a novel method for studying microbial composition. Microb Ecol Health Dis 26:27663. https://doi.org/10.3402/mehd.v26.27663.
    • (2015) Microb Ecol Health Dis , vol.26 , pp. 27663
    • Mandal, S.1    Van Treuren, W.2    White, R.A.3    Eggesbø, M.4    Knight, R.5    Peddada, S.D.6
  • 13
    • 33646244766 scopus 로고    scopus 로고
    • Groups of parts and their balances in compositional data analysis
    • Egozcue JJ. 2005. Groups of parts and their balances in compositional data analysis. Math Geol 37:795-828.
    • (2005) Math Geol , vol.37 , pp. 795-828
    • Egozcue, J.J.1
  • 14
    • 84873078603 scopus 로고    scopus 로고
    • Exploring compositional data with the CoDa-dendrogram
    • Pawlowsky-Glahn V, Egozcue JJ. 2011. Exploring compositional data with the CoDa-dendrogram. Austrian J Stat 40:103-113.
    • (2011) Austrian J Stat , vol.40 , pp. 103-113
    • Pawlowsky-Glahn, V.1    Egozcue, J.J.2
  • 15
    • 85041667899 scopus 로고    scopus 로고
    • A phylogenetic transform enhances analysis of compositional microbiota data
    • Silverman JD, Washburne A, Mukherjee S, David LA. 2016. A phylogenetic transform enhances analysis of compositional microbiota data. bioRxiv https://doi.org/10.1101/072413.
    • (2016) BioRxiv
    • Silverman, J.D.1    Washburne, A.2    Mukherjee, S.3    David, L.A.4
  • 17
    • 67651247607 scopus 로고    scopus 로고
    • Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale
    • Lauber CL, Hamady M, Knight R, Fierer N. 2009. Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale. Appl Environ Microbiol 75:5111-5120. https://doi.org/10.1128/AEM.00335-09.
    • (2009) Appl Environ Microbiol , vol.75 , pp. 5111-5120
    • Lauber, C.L.1    Hamady, M.2    Knight, R.3    Fierer, N.4
  • 19
    • 84979917605 scopus 로고    scopus 로고
    • Regression analysis for microbiome compositional data
    • Shi P, Zhang A, Li H. 2016. Regression analysis for microbiome compositional data. Ann Appl Stat 10:1019-1040. https://doi.org/10.1214/16-AOAS928.
    • (2016) Ann Appl Stat , vol.10 , pp. 1019-1040
    • Shi, P.1    Zhang, A.2    Li, H.3
  • 20
    • 84925043393 scopus 로고    scopus 로고
    • A Winogradsky-based culture system shows an association between microbial fermentation and cystic fibrosis exacerbation
    • Quinn RA, Whiteson K, Lim Y, Salamon P, Bailey B, Mienardi S, Sanchez SE, Blake D, Conrad D, Rohwer F. 2015. A Winogradsky-based culture system shows an association between microbial fermentation and cystic fibrosis exacerbation. ISME J 9:1024-1038. https://doi.org/10.1038/ismej.2014.234.
    • (2015) ISME J , vol.9 , pp. 1024-1038
    • Quinn, R.A.1    Whiteson, K.2    Lim, Y.3    Salamon, P.4    Bailey, B.5    Mienardi, S.6    Sanchez, S.E.7    Blake, D.8    Conrad, D.9    Rohwer, F.10
  • 21
    • 0742305770 scopus 로고    scopus 로고
    • Isometric logratio transformations for compositional data analysis
    • Egozcue JJ, Barcel C. 2003. Isometric logratio transformations for compositional data analysis. Math Geol 35:279-300.
    • (2003) Math Geol , vol.35 , pp. 279-300
    • Egozcue, J.J.1    Barcel, C.2
  • 23
    • 84901363655 scopus 로고    scopus 로고
    • Waste not, want not: Why rarefying microbiome data is inadmissible
    • McMurdie PJ, Holmes S. 2014. Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput Biol 10:e1003531. https://doi.org/10.1371/journal.pcbi.1003531.
    • (2014) PLoS Comput Biol , vol.10 , pp. e1003531
    • McMurdie, P.J.1    Holmes, S.2
  • 25
    • 0742267880 scopus 로고    scopus 로고
    • Dealing with zeros and missing values in compositional data sets using nonparametric imputation
    • Martín-Fernández JA, Barceló-Vidal C, Pawlowsky-Glahn V. 2003. Dealing with zeros and missing values in compositional data sets using nonparametric imputation. Math Geol 35:253-278.
    • (2003) Math Geol , vol.35 , pp. 253-278
    • Martín-Fernández, J.A.1    Barceló-Vidal, C.2    Pawlowsky-Glahn, V.3
  • 26
    • 84862276328 scopus 로고    scopus 로고
    • Structure, function and diversity of the healthy human microbiome
    • Human Microbiome Project Consortium
    • Human Microbiome Project Consortium. 2012. Structure, function and diversity of the healthy human microbiome. Nature 486:207-214. https://doi.org/10.1038/nature11234.
    • (2012) Nature , vol.486 , pp. 207-214


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.