Thank you Philipp for sharing. I am particularly interested in the modified PCA that maximizes shape variation around the symmetric origin rather than the sample mean.
May I ask can the following line of R code be implemented for this purpose: prcomp(x, retx = TRUE, *center = FALSE*, scale. = FALSE, tol = NULL, rank. = NULL, …) where x is a matrix containing asymmetry vectors (shape difference between original and relabled reflections) for all specimens with n (number of specimens) rows and p*k columns (p landmarks in k dimensions). Is the above R code correct? If I understand correctly, the center argument should be set to F, then what about the scale. argument? Best regards, Lv On Wednesday, 29 April 2020 23:04:45 UTC+8, mitterp3 wrote: > > Dear morphometricians, > > > I hope you are all doing well in these difficult times! > > > I would like to draw your attention to some morphometrics-related papers > that we published this year. > > > Mitteroecker P, Bartsch S, Erkinger C, Grunstra NDS, Le Maître A, > Bookstein FL (2020) Morphometric Variation at Different Spatial Scales: > Coordination and Compensation in the Emergence of Organismal Form. > Systematic Biology, early view, https://doi.org/10.1093/sysbio/syaa007 > > > In this paper we introduce a new approach for studying integration and > canalization of size and shape variation (partly derived from Fred's work > on self-similar shape distributions). It is based on the idea that if > anatomical elements vary independently, then their variation accumulates at > larger scales (or for composite structures). Quantifying size or shape > variation relative to its spatial scale thus allows for the identification > of coordinating or compensating processes during development and evolution. > > > Neubauer S, Gunz P, Scott NA, Hublin J-J, Mitteroecker P (2020) Evolution > of brain lateralization: a shared hominid pattern of endocranial asymmetry > is much more variable in humans than in great apes. Science Advances > 6(7):eaax9935 > > > In this paper we present a multivariate analysis of shape asymmetry with a > slightly modified version of PCA that maximizes shape variation around the > symmetric origin, not the sample mean. > > > Mitteroecker P (2020) Morphometrics in Evolutionary Developmental Biology. > In: Nuno de la Rosa L, Müller G (eds) Evolutionary Developmental Biology. > Springer, Cham > > > This is a brief review of geometric morphometrics in evolutionary > developmental biology. > > > Best wishes, > > > Philipp > > > https://www.researchgate.net/profile/Philipp_Mitteroecker > -- You received this message because you are subscribed to the Google Groups "Morphmet" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To view this discussion on the web visit https://groups.google.com/d/msgid/morphmet2/b1cf4d90-c9b5-4e11-977a-677f791df2f1%40googlegroups.com.
