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dkim=pass header.i=@uwnetid.onmicrosoft.com header.s=selector1-uw-edu header.b=uromKtBq; spf=pass (google.com: domain of m...@uw.edu designates 140.142.234.176 as permitted sender) smtp.mailfrom=m...@uw.edu Precedence: list Mailing-list: list morphmet@morphometrics.org; contact morphmet+own...@morphometrics.org List-ID: <morphmet.morphometrics.org> X-Spam-Checked-In-Group: morphmet@morphometrics.org X-Google-Group-Id: 545891634474 List-Post: <https://groups.google.com/a/morphometrics.org/group/morphmet/post>, <mailto:morphmet@morphometrics.org> List-Help: <https://support.google.com/a/morphometrics.org/bin/topic.py?topic=25838>, <mailto:morphmet+h...@morphometrics.org> List-Archive: <https://groups.google.com/a/morphometrics.org/group/morphmet/> List-Unsubscribe: <mailto:googlegroups-manage+545891634474+unsubscr...@googlegroups.com>, <https://groups.google.com/a/morphometrics.org/group/morphmet/subscribe> X-MXTHUNDER-Identifier: <mwhpr08mb289444026dd9b2ca13516483a8...@mwhpr08mb2894.namprd08.prod.outlook.com> X-MXTHUNDER-IP-Rating: 1, 140.142.234.176, Ugly c=0.165853 p=0.2 Source Normal X-MXTHUNDER-Scan-Result: 0 X-MXTHUNDER-Rules: 0-0-0-32767-c X-MXTHUNDER-Clean: Yes X-MXTHUNDER-Group: OK
This has been an interesting discussion. Hopefully it has been useful to th= e newcomers to the GMM and shape analyses to better understand some of the = challenges they are likely to face. I think the issues of homology, semi-la= ndmarks, number of variables vs number of samples routinely discussed here = because ultimately there is no hard rule to abide by, but realities to live= with (sample sizes may not be increased) and trade-offs to be made. I like= Benedikt's argument about biological pragmatism.=20 I do not want to hijack the thread and the topic, but wanted to briefly ref= lect on Benedikt's comments atlas based methods. Image based analyses, when= coupled with a computationally derived anatomical atlas, do offer a promis= e of automating some aspects of the acquiring information on morphology fro= m volumetric scans. This approach can be particularly powerful, and appeali= ng if one is working with a very large number of individuals (>>100) of the= same species and of similar developmental stage. I find this approach very= useful in tedious preprocessing steps (segmentation, rigidly aligning samp= les to a fixed anatomical orientation say to make standardized 3D rendering= s of all samples to visually assess phenotypic variability, etc), basically= in processes that can tolerate large margin of error. Whether they can ful= ly replace landmark based analyses (or result in fully automated landmarkin= g procedures), I am not entirely sure. Basically, it boils down to the fact= that there is no independent assessment of how well the registration perfo= rmed, apart from the visual inspection of how well the template deformed in= to the sample (or the other way around depending on the task). The choice o= f image similarity metrics (along with many other parameters than can be tu= ned) can result in different outcomes. Even in the well-chewed domain of hu= man neuroimaging validation of non-linear image registration remains a big = issue. They typically resort to ranking algorithms on how well they approac= h to the manually segmented reference datasets. Since atlas-based landmarki= ng is essentially an image segmentation process, we do need to assess how w= ell registration simulated the human observer's landmark placement if we ar= e to justify using one method over another.=20 While, I agree with Benedikt's comment "measure the biological effects of i= nterest rather than how well they simulate the behavior of manually placed = landmarks" in principal, I am not entirely sure how one can go about this w= ithout knowing what the biological effects of interests are beforehand, bec= ause we wouldn't know what we measured. M -----Original Message----- From: Benedikt Hallgrimsson <bhall...@ucalgary.ca>=20 Sent: Thursday, November 8, 2018 11:32 AM To: Adams, Dean [EEOBS] <dcad...@iastate.edu>; andrea cardini <alcardini@gm= ail.com>; morphmet@morphometrics.org Subject: RE: [MORPHMET] Re: semilandmarks in biology Dear Colleagues, So I=E2=80=99ve been wondering whether to wade into this issue.. =20 There seems to be an undercurrent here of mathematics vs biology, but I sus= pect that the real issue here is probably morphometric theory versus the pr= agmatic compromises necessary when using morphometric tools to answer biolo= gical questions. Others on this thread have thought (and written) much mor= e deeply about the interface of morphometric theory and biology than I have= , but for what it=E2=80=99s worth, here are my two cents on this issue. Fu= ndamentally, what is most important is that quantifications of morphology c= apture relevant biological variation while avoiding artifacts that can skew= or mislead interpretation. That matters much more to than whether there is= real homology or not. I'm not even sure what "real homology" for landmark = coordinate data means in a biological sense, even for Type 1 landmarks. Th= e "identity" or homology of landmarks tends to become messy pretty quickly = when the underlying developmental biology is examined closely. I think Paul= O'Higgins gave a great talk once on that basic theme if I remember correct= ly. Chris Percival also did a nice analysis showing how apparently obviousl= y homologous landmarks that occur at intersections of major components of t= he face can drift in terms of the origin of the underlying tissue during de= velopment. So, I think we may sometimes get too hung up on this ideal that = the points that we place on morphological structures actually represent som= ething real. They are simply intended to quantify morphology within the con= text of a biological question. It's not landmarks but rather the patterns = of variation that an analysis generates are the objective basis of study an= d those patterns are only objective within the context of a biological ques= tion. The key issue is avoiding artifacts that can influence biological int= erpretation. In terms of this discussion, clearly semi-landmarks present one kind of cha= llenge where one has to be careful about artifacts. Another, perhaps more c= urrently relevant challenge, however, is the quantification of variation in= volumetric images or surfaces that have been nonlinearly registered to an = atlas. In this case, one can place landmarks anywhere and recover the corr= esponding location in every specimen or image. That correspondence is a sor= t of homology and those landmarks are not slid around like semi-landmarks. = However, they are not placed by an observer as distinct observations either= . These kinds of points behave fairly similarly to manually placed points = (albeit without measurement error and with artifacts that appear as one tri= es to register increasingly dissimilar shapes). However, I think that, dri= ven by the needs of the biological questions, we are increasingly going to = be using this kind of automated quantification of morphology in morphometri= c analyses, so we need to think carefully about how to validate such data. = My own bias here is that appropriate validations address how well (and this= can be defined contextually) such quantifications measure the biological e= ffects of interest rather than how well they simulate the behavior of manua= lly placed landmarks.=20 I suppose this is an argument for biological pragmatism, but I hope some fi= nd this useful.=20 Benedikt -----Original Message----- From: Adams, Dean [EEOBS] <dcad...@iastate.edu> Sent: Wednesday, November 7, 2018 6:48 AM To: andrea cardini <alcard...@gmail.com>; morphmet@morphometrics.org Subject: RE: [MORPHMET] Re: semilandmarks in biology Folks, =20 I think it is important to recognize that the example in Andrea=E2=80=99s e= arlier post does not really address the validity of sliding semilandmark me= thods, because all of the data were simulated using isotropic error. Thus, = the points called semilandmarks in that example were actually independent o= f one another at the outset. =20 Yet a major reason for using semilandmark approaches is the fact that point= s along curves and surfaces covary precisely because they are describing th= ose structures. Thus, this interdependence must be accounted for before sha= pes are compared between objects. The original literature on semilandmark m= ethods makes this, and related issues quite clear. =20 What that means is that evaluating semilandmark methods requires simulation= s where the points on curves are simulated with known input covariance base= d on the curve itself (difficult, but not impossible to do). But using inde= pendent error will not accomplish this. =20 The result is that treating fixed landmarks as semilandmarks can lead to wh= at some feel are unintended outcomes, just as treating semilandmarks as fix= ed points are known to do (illustrated nicely in Figs 1-4 of Gunz et al. 20= 05). But both are mis-applications of methods, not indictments of them.=20 As to the other points in the thread (the number of semilandmark points, et= c.), earlier posts by Jim, Philipp, and Mike have addressed these. =20 Dean Dr. Dean C. Adams Director of Graduate Education, EEB Program Professor Department of Ecology= , Evolution, and Organismal Biology Iowa State University www.public.iastat= e.edu/~dcadams/ phone: 515-294-3834 -----Original Message----- From: andrea cardini <alcard...@gmail.com> Sent: Wednesday, November 7, 2018 4:31 AM To: morphmet@morphometrics.org Subject: Re: [MORPHMET] Re: semilandmarks in biology Making cool pictures has a purpose only if both the pics and the numbers be= hind them are accurate. It's not an aim in itself, I hope (although this is= the second time I hear that one should add as many points as needed to see= a nice picture). Parsimonious explanations are, to me, much more appealing= than nice pictures (as much as I like a beautiful visualization), but that= might be a matter of taste. Philipp, could you clarify what "homology function" means? We're not saying that sliding creates homology, as I sometimes read in pape= rs, are we? No doubt one does not expect anatomical regions of an organism to be indepe= ndent. The open question to me is what the biological covariance is and wha= t is the bit added by superimposing and maybe sliding. I suspect that on th= is there's no universal answer: it will be dependent on the study organism,= the number and distribution (and type) of landmarks etc. In some studies i= t might not matter much, but in others may be much more relevant. Thanks all for the comments. Cheers Andrea On 06/11/2018 20:53, mitte...@univie.ac.at wrote: > Yes, it was always well known that sliding adds covariance but this is=20 > irrelevant for most studies, especially for group mean comparisons and=20 > shape regressions: the kind of studies for which GMM is most=20 > efficient, as Jim noted. > If you consider the change of variance-covariance structure due to (a=20 > small amount of) sliding as an approximately linear transformation,=20 > then the sliding is also largely irrelevant for CVA, relative PCA,=20 > Mahalanobis distance and the resulting group classifications, as they=20 > are all based on the relative eigenvalues of two covariance matrices=20 > and thus unaffected by linear transformations. In other words, in the=20 > lack of a reasonable biological null model, the interpretation of a=20 > single covariance structure is very difficult, but the way in which=20 > one covariance structure deviates from another can be interpreted much ea= sier. >=20 > Concerning your example: The point is that there is no useful model of=20 > "totally random data" (but see Bookstein 2015 Evol Biol). Complete=20 > statistical independence of shape coordinates is geometrically=20 > impossible and biologically absurd. Under which biological (null)=20 > model can two parts of a body, especially two traits on a single=20 > skeletal element such as the cranium, be complete uncorrelated? >=20 > Clearly, semilandmarks are not always necessary, but making "cool=20 > pictures" can be quite important in its own right for making good=20 > biology, especially in exploratory settings. Isn't the visualization=20 > one of the primary strengths of geometric morphometrics? >=20 > It is perhaps also worth noting that one can avoid a good deal of the=20 > additional covariance resulting from sliding. Sliding via minimizing=20 > bending energy introduces covariance in the position of the=20 > semilandmarks _along_ the curve/surface. In some of his analyses, Fred=20 > Bookstein just included the coordinate perpendicular to the=20 > curve/surface for the semilandmarks, thus discarding a large part of=20 > the covariance. Note also that sliding via minimizing Procrustes=20 > distance introduces only little covariance among semilandmarks because=20 > Procrustes distance is minimized independently for each semilandmark=20 > (but the homology function implied here is biologically not so appealing)= . >=20 > Best, >=20 > Philipp >=20 >=20 >=20 > Am Dienstag, 6. November 2018 18:34:51 UTC+1 schrieb alcardini: >=20 > Yes, but doesn't that also add more covariance that wasn't there in > the first place? > Neither least squares nor minimum bending energy, that we minimize fo= r > sliding, are biological models: they will reduce variance but will do > it in ways that are totally biologically arbitrary. >=20 > In the examples I showed sliding led to the appearance of patterns > from totally random data and that effect was much stronger than > without sliding. > I neither advocate sliding or not sliding. Semilandmarks are differen= t > from landmarks and more is not necessarily better. There are > definitely some applications where I find them very useful but many > more where they seem to be there just to make cool pictures. >=20 > As Mike said, we've already had this discussion. Besides different > views on what to measure and why, at that time I hadn't appreciated > the problem with p/n and the potential strength of the patterns > introduced by the covariance created by the superimposition (plus > sliding!). >=20 > Cheers >=20 > Andrea >=20 > On 06/11/2018, F. James Rohlf <f.jame...@stonybrook.edu > <javascript:>> wrote: > > I agree with Philipp but I would like to add that the way I think > about the > > justification for the sliding of semilandmarks is that if one > were smart > > enough to know exactly where the most meaningful locations are > along some > > curve then one should just place the points along the curve and > > computationally treat them as fixed landmarks. However, if their > exact > > positions are to some extend arbitrary (usually the case) > although still > > along a defined curve then sliding makes sense to me as it > minimizes the > > apparent differences among specimens (the sliding minimizes your > measure of > > how much specimens differ from each other or, usually, the mean > shape. > > > > > > > > _ _ _ _ _ _ _ _ _ > > > > F. James Rohlf, Distinguished Prof. Emeritus > > > > > > > > Depts. of Anthropology and of Ecology & Evolution > > > > > > > > > > > > From: mitt...@univie.ac.at <javascript:> <mitt...@univie.ac.at > <javascript:>> > > Sent: Tuesday, November 6, 2018 9:09 AM > > To: MORPHMET <morp...@morphometrics.org <javascript:>> > > Subject: [MORPHMET] Re: semilandmarks in biology > > > > > > > > I agree only in part. > > > > > > > > Whether or not semilandmarks "really are needed" may be hard to sa= y > > beforehand. If the signal is known well enough before the study, > even a > > single linear distance or distance ratio may suffice. In fact, mos= t > > geometric morphometric studies are characterized by an > oversampling of > > (anatomical) landmarks as an exploratory strategy: it allows for > unexpected > > findings (and nice visualizations). > > > > > > > > Furthermore, there is a fundamental difference between sliding > semilandmarks > > and other outline methods, including EFA. When establishing > correspondence > > of semilandmarks across individuals, the minBE sliding algorithm > takes the > > anatomical landmarks (and their stronger biological homology) > into account, > > while standard EFA and related techniques cannot easily combine > point > > homology with curve or surface homology. Clearly, when point > homology > > exists, it should be parameterized accordingly. If smooth curves > or surfaces > > exists, they should also be parameterized, whether or not this > makes the > > analysis slightly more challenging. > > > > > > > > Anyway, different landmarks often convey different biological > signals and > > different homology criteria. For instance, Type I and Type II > landmarks > > (sensu Bookstein 1991) differ fundamentally in their notion of > homology. > > Whereas Type I landmarks are defined in terms of local anatomy or > histology, > > a Type II landmark is a purely geometric construct, which may or > may not > > coincide with notions of anatomical/developmental homology. ANY > reasonable > > morphometric analysis must be interpreted in the light of the > correspondence > > function employed, and the some holds true for semilandmarks. For > this, of > > course, one needs to understand the basic properties of sliding > landmarks, > > much as the basic properties of Procrustes alignment, etc.. For > instance, > > both the sliding algorithm and Procrustes alignment introduce > correlations > > between shape coordinates (hence their reduced degrees of > freedom). This is > > one of the reasons why I have warned for many years and in many > publications > > about the biological interpretation of raw correlations (e.g., > summarized in > > Mitteroecker et al. 2012 Evol Biol). Interpretations in terms of > > morphological integration or modularity are even more difficult > because in > > most studies these concepts are not operationalized. They are eith= er > > described by vague and biologically trivial narratives, or they ar= e > > themselves defined as patterns of correlations, which is circular > and makes > > most "hypotheses" untestable. > > > > > > > > The same criticism applies to the naive interpretation of PCA > scree plots > > and derived statistics. An isotropic (circular) distribution of > shape > > coordinates corresponds to no biological model or hypothesis > whatsoever > > (e.g., Huttegger & Mitteroecker 2011, Bookstein & Mitteroecker > 2014, and > > Bookstein 2015, all three in Evol Biol). Accordingly, a deviation > from > > isometry does not itself inform about integration or modularity > (in any > > reasonable biological sense). > > > > The multivariate distribution of shape coordinates, including > "dominant > > directions of variation," depend on many arbitrary factors, > including the > > spacing, superimposition, and sliding of landmarks as well as on > the number > > of landmarks relative to the number of cases. But all of this > applies to > > both anatomical landmarks and sliding semilandmarks. > > > > > > > > I don't understand how the fact that semilandmarks makes some of > these > > issues more obvious is an argument against their use. > > > > > > > > Best, > > > > > > > > Philipp > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > Am Dienstag, 6. November 2018 13:28:55 UTC+1 schrieb alcardini: > > > > As a biologist, for me, the question about whether or not to use > > semilandmarks starts with whether I really need them and what > they're > > actually measuring. > > > > On this, among others, Klingenberg, O'Higgins and Oxnard have > written some > > very important easy-to-read papers that everyone doing > morphometrics should > > consider and carefully ponder. They can be found at: > > https://preview.tinyurl.com/semilandmarks > <https://preview.tinyurl.com/semilandmarks> > > > > I've included there also an older criticism by O'Higgins on EFA > and related > > methods. As semilandmarks, EFA and similar methods for the > analysis of > > outlines measure curves (or surfaces) where landmarks might be > few or > > missing: if semilandmarks are OK because where the points map is > irrelevant, > > as long as they capture homologous curves or surfaces, the same > applies for > > EFAs and related methods; however, the opposite is also true and, > if there > > are problems with 'homology' in EFA etc., those problems are > there also > > using semilandmarks as a trick to discretize curves and surfaces. > > > > Even with those problems, one could still have valid reasons to us= e > > semilandmarks but it should be honestly acknowledged that they > are the best > > we can do (for now at least) in very difficult cases. Most of the > studies I > > know (certainly a minority from a now huge literature) seem to > only provide > > post-hoc justification of the putative importance of > semilandmarks: there > > were few 'good landmarks'; I added semilandmarks and found > something; > > therefore they work. > > > > > > > > From a mathematical point of view, I cannot say anything, as I am > not a > > mathematician. On this, although not specific to semilandmarks, a > > fundamental reading for me is Bookstein, 2017, Evol Biol (also > available for > > a few days, as the other pdfs, at the link above). That paper is > one of the > > most inspiring I've ever read and it did inspire a small section > of my > > recent Evol Biol paper on false positives in some of the tests of > > modularity/integration using Procrustes data. For analyses using > sliding > > semilandmarks, the relevant figures are Figs 4-5, that suggest > how tricky > > things can be. If someone worries that that's specific to my > example data > > (and it could be!), the experiment is trivial to repeat on > anyone's own > > semilandmark data. > > > > Taken from the data of the same paper, below you find a PCA of > rodent > > hemimandibles (adults, within a species) using minBE slid > semilandmarks or > > just 9 'corresponding' landmarks. The advantage of semilandmarks, > compared > > to the 9 landmarks, is that they allow to capture a dominant > direction of > > variation (PC1 accounting for 14% of shape variance), whose > positive extreme > > (magnified 3 times) is shown with a really suggestive deformation > grid > > diagram. In comparison, 9 landmarks do not suggest any dominant > direction of > > variation (each PC explaining 9-5% of variance), the scatterplot > is circular > > and the TPS shape diagram much harder to interpret. > > > > What these two PCAs have in common is that they are both analyses > of random > > noise (multivariate random normally distributed numbers added to > a mean > > shape). > > > > > > > > All the best > > > > > > > > Andrea > > > > > > > > 9 LANDMARKS PLUS 22 SLID SEMILANDMARKS > > > > > > > =20 > <https://groups.google.com/a/morphometrics.org/group/morphmet/attach/d > cce33d95d952/oclbeaidoponnmni.jpeg?part=3D0.1.1&view=3D1&authuser=3D0 > =20 > <https://groups.google.com/a/morphometrics.org/group/morphmet/attach/d > cce33d95d952/oclbeaidoponnmni.jpeg?part=3D0.1.1&view=3D1&authuser=3D0>> >=20 > > > > > > 9 LANDMARKS > > > > > > > =20 > <https://groups.google.com/a/morphometrics.org/group/morphmet/attach/d > cce33d95d952/pebddfgpogepigmi.jpeg?part=3D0.1.2&view=3D1&authuser=3D0 > =20 > <https://groups.google.com/a/morphometrics.org/group/morphmet/attach/d > cce33d95d952/pebddfgpogepigmi.jpeg?part=3D0.1.2&view=3D1&authuser=3D0>> >=20 > > > > > > -- > > > > Dr. Andrea Cardini > > Researcher, Dipartimento di Scienze Chimiche e Geologiche, > Universit=C3=A0 di > > Modena e Reggio Emilia, Via Campi, 103 - 41125 Modena - Italy > > tel. 0039 059 2058472 > > > > Adjunct Associate Professor, School of Anatomy, Physiology and Hum= an > > Biology, The University of Western Australia, 35 Stirling > Highway, Crawley > > WA 6009, Australia > > > > E-mail address: alca...@gmail.com <javascript:> , > andrea....@unimore.it > > <javascript:> > > WEBPAGE: https://sites.google.com/site/alcardini/home/main > <https://sites.google.com/site/alcardini/home/main> > > > > FREE Yellow BOOK on Geometric Morphometrics: > > https://tinyurl.com/2013-Yellow-Book > <https://tinyurl.com/2013-Yellow-Book> > > > > ESTIMATE YOUR GLOBAL FOOTPRINT: > > > http://www.footprintnetwork.org/en/index.php/GFN/page/calculators/ > <http://www.footprintnetwork.org/en/index.php/GFN/page/calculators/> > > > > -- > > MORPHMET may be accessed via its webpage at > http://www.morphometrics.org > > --- > > 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 morphmet+u...@morphometrics.org <javascript:> > > <mailto:morphmet+u...@morphometrics.org <javascript:>> . > > > > -- > > MORPHMET may be accessed via its webpage at > http://www.morphometrics.org > > --- > > 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 morphmet+u...@morphometrics.org <javascript:>. > > >=20 >=20 > -- >=20 > Dr. Andrea Cardini > Researcher, Dipartimento di Scienze Chimiche e Geologiche, Universit= =C3=A0 > di Modena e Reggio Emilia, Via Campi, 103 - 41125 Modena - Italy > tel. 0039 059 2058472 >=20 > Adjunct Associate Professor, School of Anatomy, Physiology and Human > Biology, The University of Western Australia, 35 Stirling Highway, > Crawley WA 6009, Australia >=20 > E-mail address: alca...@gmail.com <javascript:>, > andrea....@unimore.it <javascript:> > WEBPAGE: https://sites.google.com/site/alcardini/home/main > <https://sites.google.com/site/alcardini/home/main> >=20 > FREE Yellow BOOK on Geometric Morphometrics: > =20 > http://www.italian-journal-of-mammalogy.it/public/journals/3/issue_241 > _complete_100.pdf > =20 > <http://www.italian-journal-of-mammalogy.it/public/journals/3/issue_24 > 1_complete_100.pdf> >=20 >=20 > ESTIMATE YOUR GLOBAL FOOTPRINT: > http://www.footprintnetwork.org/en/index.php/GFN/page/calculators/ > =20 > <http://www.footprintnetwork.org/en/index.php/GFN/page/calculators/> >=20 > -- > MORPHMET may be accessed via its webpage at=20 > http://www.morphometrics.org > --- > You received this message because you are subscribed to the Google=20 > Groups "MORPHMET" group. > To unsubscribe from this group and stop receiving emails from it, send=20 > an email to morphmet+unsubscr...@morphometrics.org > <mailto:morphmet+unsubscr...@morphometrics.org>. --=20 Dr. Andrea Cardini Researcher, Dipartimento di Scienze Chimiche e Geologiche, Universit=C3=A0 = di Modena e Reggio Emilia, Via Campi, 103 - 41125 Modena - Italy tel. 0039 = 059 2058472 Adjunct Associate Professor, School of Anatomy, Physiology and Human Biolog= y, The University of Western Australia, 35 Stirling Highway, Crawley WA 600= 9, Australia E-mail address: alcard...@gmail.com, andrea.card...@unimore.it WEBPAGE: https://sites.google.com/site/alcardini/home/main FREE Yellow BOOK on Geometric Morphometrics:=20 https://tinyurl.com/2013-Yellow-Book ESTIMATE YOUR GLOBAL FOOTPRINT:=20 http://www.footprintnetwork.org/en/index.php/GFN/page/calculators/ -- MORPHMET may be accessed via its webpage at http://www.morphometrics.org --- 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 e= mail to morphmet+unsubscr...@morphometrics.org. -- MORPHMET may be accessed via its webpage at http://www.morphometrics.org --- 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 e= mail to morphmet+unsubscr...@morphometrics.org. -- MORPHMET may be accessed via its webpage at http://www.morphometrics.org --- 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 e= mail to morphmet+unsubscr...@morphometrics.org. --=20 MORPHMET may be accessed via its webpage at http://www.morphometrics.org ---=20 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 e= mail to morphmet+unsubscr...@morphometrics.org.
