Correction: Uncovering the horseshoe effect in microbial analyses (mSystems (2017) 2:1 (e00166-16) DOI: 10.1128/mSystems.00166-16);Uncovering the horseshoe effect in microbial analyses

mSystems

Volumn 2, Issue 1, 2017, Pages

  Morton, James T ^a,b   Toran, Liam ^c   Edlund, Anna ^d   Metcalf, Jessica L ^e   Lauber, Christian ^f   Knight, Rob ^a,b  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b UNIVERSITY OF CALIFORNIA SAN DIEGO   (United States)

^c UNIVERSITÉ DE LYON   (France)

^d J CRAIG VENTER INSTITUTE   (United States)

^e Department of Environmental and Radiological Health Sciences   (United States)

^f NESTLÉ RESEARCH CENTER   (Switzerland)

Author keywords

Decomposition; Horseshoe; Microbial ecology; PH; Soil

Indexed keywords

EID: 85034013111     PISSN: None     EISSN: 23795077     Source Type: Journal    
DOI: 10.1128/mSystems.00006-18     Document Type: Erratum

References (14)

1. Legendre P, Legendre L. 1998. Numerical ecology 2nd ed. Elsevier Science, Amsterdam, Netherlands.
2. Podani J, Miklós I. 2002. Resemblance coefficients and the horseshoe effect in principal coordinates analysis. Ecology 83:3331-3343. https://doi.org/10.1890/0012-9658(2002)083[3331:RCATHE]2.0.CO;2.
3. Hill MO, Gauch HG, Jr. 1980. Detrended correspondence analysis: an improved ordination technique. Vegetatio 42:47-58. https://doi.org/10.1007/BF00048870.
4. Ejrnæs R. 2000. Can we trust gradients extracted by detrended correspondence analysis? J Veg Sci 11:565-572. https://doi.org/10.2307/3246586.
5. Disconis P, Goel S, Holmes S. 2008. Horseshoes in multidimensional scaling and local kernel methods. Ann Appl Stat 2:777-807.
6. Camiz S. 2005. The Guttman effect: its interpretation and a new redressing method. https://www.researchgate.net/publication/228760485 -The-Guttman-effect-Its-interpretation-and-a-new-redressing-method.
7. Smith JM, Smith NH. 1996. Synonymous nucleotide divergence: what is "saturation"? Genetics 142:1033-1036.
8. Tourasse NJ, Gouy M. 1997. Evolutionary distances between nucleotide sequences based on the distribution of substitution rates among sites as estimated by parsimony. Mol Biol Evol 14:287-298. https://doi.org/10.1093/oxfordjournals.molbev.a025764.
9. Kuczynski J, Liu Z, Lozupone C, McDonald D, Fierer N, Knight R. 2010. Microbial community resemblance methods differ in their ability to detect biologically relevant patterns. Nat Methods 7:813-819. https://doi.org/10.1038/nmeth.1499.
10. 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.
11. Greenacre M. 1984, Theory and applications of correspondence analysis. Academic Press, Inc., New York, NY.
12. Metcalf JL, Xu ZZ, Weiss S, Lax S, Van Treuren W, Hyde ER, Song SJ, Amir A, Larsen P, Sangwan N, Haarmann D, Humphrey GC, Ackermann G, Thompson LR, Lauber C, Bibat A, Nicholas C, Gebert MJ, Petrosino JF, Reed SC, Gilbert JA, Lynne AM, Bucheli SR, Carter DO, Knight R. 2016. Mammalian corpse decomposition. Science 351:158-162. https://doi.org/10.1126/science.aad2646.
13. Lozupone C, Knight R. 2005. UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 71: 8228-8235. https://doi.org/10.1128/AEM.71.12.8228-8235.2005.
14. Levina E, Bickel P. 2001. The earth mover's distance is the Mallows distance: some insights from statistics, p 251-256. In Proceedings Eighth IEEE International Conference on Computer Vision, 2001. ICCV 2001. https://doi.org/10.1109/ICCV.2001.937632.