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Classifying hot water chemistry: Application of MULTIVARIATE STATISTICS - Dataset
<p>These files are the dataset for the following paper "Classifying hot water chemistry: Application of MULTIVARIATE STATISTICS". Authors: Prihadi Sumintadireja<sup>1</sup>, Dasapta Erwin Irawan<sup>1</sup>, Yuano Rezky<sup>2</sup>, Prana Ugiana Gio<sup>3, </sup>Anggita Agustin<sup>1</sup></p>
FIGURE 1. Scatterplots from multivariate statistical analyses. Ellipses define the 95 in Morphological Variation in a Unisexual Whiptail Lizard (Aspidoscelis exsanguis) and One of Its Bisexual Parental Species (Aspidoscelis inornata) (Reptilia: Squamata: Teiidae): Is the Clonal Species Less Variable?
FIGURE 1. Scatterplots from multivariate statistical analyses. Ellipses define the 95% confidence limits of score distributions. A. Principal component scores of 14 field A. exsanguis, 42 laboratory A. exsanguis of two lineages pooled, and 19 field A. inornata. Axis percentages reflect variance explained by PC1 and PC2 (table 5). B. Canonical variate scores of the same specimens as in A. Axis percentages are relative contributions of CV1 and CV2 to the discrimination (table 5).
Multivariate Genome-wide association summary statistics for shared aging factor
<p>This dataset contains genome-wide summary statistics (autosomal variants) computed from a multivariate genome-wide association study of five aging-related phenotypes using Genomic Structural Equation Modeling (https://github.com/GenomicSEM/GenomicSEM). The effective sample size is calculated to be 1,958,774. Column descriptions are included in the accompanying README file. </p> <p>The summary statistics are provided on an "AS-IS" basis, without any type of warranty, expressed or implied, including but not limited to any warranty as to their performance, merchantability, or fitness for any particular purpose.</p> <p>If investigators use these data, any and all consequences are entirely their responsibility. The user agrees that to cite the appropriate publication in any communications or publications arising directly or indirectly from these data by downloading and and using these data,. The user also agrees to respect the requested responsibilities of resource users under 2003 Fort Lauderdale principles and also agree that they will never attempt to identify any participant.</p> <p> </p>
Figure 13 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 13. Multivariate variation in the eight interlandmark distances measured between ventroglandularia V1, V2 and V3 in posterior view (distance set 3). A, scatter plot of canonical variate scores (root 1 vs. root 2), distances with highest standardized factors are illustrated for both axes. B, overall pattern of similarity among 11 Megaluracarus species and two Dadayella species based on Mahalanobis distances computed from the canonical variate analysis. This UPGMA phenogram (unweighted-pair grouping method using averages) groups the nine character states discovered in the set of distances from the ventroglandularia. Branches are labelled according to discrimination order defined by the canonical variates. Symbols in the plot and in the phenogram are as listed in Figure 11.
Figure 12 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 12. Multivariate variation in the 15 interlandmark distances measured between postocularia R2 and dorsoglandularia D2, D3 and D4 (distance set 2). (A) scatter plot of canonical variate scores (root 1 vs. root 2); distances with the highest standardized factors are illustrated for both axes. (B) overall pattern of similarity among 11 Megaluracarus species and two Dadayella species based on Mahalanobis distances computed from the canonical variate analysis. This UPGMA phenogram (unweighted-pair grouping method using averages) groups the 13 character states discovered in the collection of distances from the postocularia and dorsoglandularia. Branches are labelled according to discrimination order defined by the canonical variates. Symbols in the plot and in the phenogram are as listed in Fig. 11.
Figure 11 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 11. Multivariate variation in the 13 interlandmark distances sampled from the dorsal view of the idiosoma (distance set 1). (A) scatter plot of canonical variate scores (root 1 vs. root 2); distances with highest standardized factors are illustrated for both axes. (B) overall pattern of similarity among 11 Megaluracarus species and two Dadayella species based on Mahalanobis distances computed from the canonical variate analysis. This UPGMA phenogram (unweighted-pair grouping method using averages) groups the 12 character states discovered in the distances from the idiosoma. Branches are labelled according to discrimination order defined by the canonical variates. Symbols in the plot and in the phenogram are as follows: open blue circles, Arrenurus (Dadayella) adrianae; open green rhombuses, Dadayella aztecus; open red squares, Arrenurus (Megaluracarus) anae; solid green triangles, Megaluracarus anitahoffmannae; open pink triangles, Megaluracarus catoi; solid black circles, Megaluracarus colitus; solid grey squares, Megaluracarus costeroae; blue asterisks, Megaluracarus maya; solid red rhombuses, Megaluracarus neoexpansus; purple plus signs, Megaluracarus olmeca; lilac endashes, Megaluracarus tabascoensis; horizontal blue lines, Megaluracarus urbanus; green hyphens, Megaluracarus zitavus.
Figure 14 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 14. Single most-parsimonious tree selected in our phylogenetic analysis of the combined morphometric data with TNT (score 95.8119). The character matrix included continuous values of three distance sets and five landmark configurations. Only one shape character, the cauda outline (data set 2), is optimized in this tree. Landmark configurations of cauda shape at terminal nodes are as observed in each species. The numbers on each configuration indicate shapes that are significantly different, as evaluated by the canonical variate analysis and MANOVA for landmark data set 2, as illustrated and labelled in Fig. 7B. In all hypothetical landmark configurations of the cauda shape at internal nodes, deformation vectors at each point indicate displacements relative to the ancestral shape as optimized with TNT.
Figure 8 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 8. Shape variation of the postocularia and dorsoglandularia D2 and D3 in dorsal view (data set 3). (A) scatter plot of canonical variate scores (root 1 vs. root 2); shape changes relative to the mean shape are shown for both roots. (B) overall pattern of shape similarity among 11 Megaluracarus species and two Dadayella species based on Mahalanobis distances computed from the canonical variate analysis. This UPGMA phenogram (unweighted-pair grouping method using averages) groups the nine character states discovered in the postocularia and dorsoglandularia. Branches are labelled according to discrimination order defined by the canonical variates. Symbols in the plot and in the phenogram are as follows: open blue circles, Arrenurus (Dadayella) adrianae; open red squares, Dadayella aztecus; open green rhombuses Arrenurus (Megaluracarus) anae; blue asterisks, Megaluracarus anitahoffmannae; solid grey squares, Megaluracarus catoi; open pink triangles, Megaluracarus colitus; solid green triangles, Megaluracarus costeroae; solid red rhombuses, Megaluracarus maya; solid black circles, Megaluracarus neoexpansus; purple plus signs, Megaluracarus olmeca; lilac en-dashes, Megaluracarus tabascoensis; horizontal blue lines, Megaluracarus urbanus; green hyphens, Megaluracarus zitavus.
Figure 4 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 4. Sets of landmark (LM) and semi-landmark (SLM) configurations designed to register the shape of the dorsal (A–D) and posterior (E) views. (A) collection of 23 points for the anterior idiosoma outline, with three LMs and 20 SLMs (data set 1). (B) chain of 17 points for the cauda outline, with three LMs and 14 SLMs (data set 2). (C) string of ten points for the postocularia R2 and dorsoglandularia D2 and D3 (data set 3). (D) configuration of four points for the dorsoglandularia D4 (data set 4). (E) Arrangement of ten points for the ventroglandularia V1, V2, and V3 (data set 5).
Figure 7 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 7. Shape variation of the cauda outline in dorsal view (data set 2). (A) scatter plot of canonical variate scores (root 1 vs. root 2), deformation grids of shape changes relative to the mean shape are shown for both axes. (B) overall pattern of shape similarity among 11 Megaluracarus species and two Dadayella species based on Mahalanobis distances computed from the canonical variate analysis. All species were significantly different from each other, and therefore 13 character states were discovered in the cauda outline. Branches in the UPGMA phenogram (unweighted-pair grouping method using averages) are labelled according to discrimination order defined by the canonical variates. Symbols in the plot and in the phenogram are as described in Fig. 6.
Figure 6 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 6. Shape variation of the anterior idiosoma outline in dorsal view (data set 1). (A) scatter plot of canonical variate scores (root 1 vs. root 2); the deformation grid shows shape changes explained by the first discriminant axis. (B) overall pattern of shape similarity among 11 Megaluracarus species and two Dadayella species based on Mahalanobis distances computed from the canonical variate analysis. This UPGMA phenogram (unweighted-pair grouping method using averages) groups the ten character states discovered in the anterior idiosoma outline. Branches are labelled according to discrimination order, as defined by the canonical variates. Symbols in the plot and in the phenogram are as follows: open blue circles, Arrenurus (Dadayella) adrianae; open red squares, Dadayella aztecus; open green rhombuses, Arrenurus (Megaluracarus) anae; red solid rhombuses, Megaluracarus anitahoffmannae; black solid circles, Megaluracarus catoi; open pink triangles, Megaluracarus colitus; horizontal blue lines, Megaluracarus costeroae; solid grey squares, Megaluracarus maya; lilac en-dashes, Megaluracarus neoexpansus; purple plus signs, Megaluracarus olmeca; blue asterisks, Megaluracarus tabascoensis; solid green triangles, Megaluracarus urbanus; green hyphens, Megaluracarus zitavus.
Figure 5 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 5. Interlandmark distances (1–36) collected in dorsal (A, B) and posterior (C) views: (A) measurements 1–13 assembled for the idiosoma (distance set 1; (B) distances 14–28 measured between postocularia R2 and dorsoglandularia D2, D3, and D4 (distance set 2); (C) measurements 29–36 between ventroglandularia V1, V2, and V3 (distance set 3). Lines indicate the interlandmark distances sampled and numbers identify each distance, as listed in Table 3. Numbers with asterisks label distances for which the mean was calculated with the measurements of left and right idiosoma sides.
Figure 1 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 1. Species of Arrenurus (Megaluracarus) included in the morphometric analyses, in dorsal view: (A) Arrenurus anae; (B) Arrenurus colitus; (C) Arrenurus neoexpansus; (D) Arrenurus zitavus; (E) Arrenurus maya; (F) Arrenurus catoi; (G) Arrenurus tabascoensis; (H) Arrenurus anitahoffmannae; (I) Arrenurus urbanus; (J) Arrenurus olmeca; (K) Arrenurus costeroae. The pairs of postocularia R2 and dorsoglandularia D2, D3, and D4 in (F) are indicated with arrows pointing at gland openings and setae insertions. Scale bars: 100 µm.
Figure 9 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 9. Shape variation of dorsoglandularia D4 in dorsal view (data set 4). (A) scatter plot of canonical variate scores (root 1 vs. root 2). (B) overall pattern of shape similarity among 11 Megaluracarus species and two Dadayella species based on Mahalanobis distances computed from the canonical variate analysis. This UPGMA phenogram (unweightedpair grouping method using averages) groups the three character states discovered in the dorsoglandularia. Branches are labelled according to discrimination order defined by the canonical variates. Symbols in the plot and in the phenogram are as listed in Fig. 8.
Figure 10 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 10. Shape variation of ventroglandularia V1, V2 and V3 (data set 5). (A) scatter plot of canonical variate scores (root 1 vs. root 2); shape changes relative to the mean shape are shown for both roots. (B) overall pattern of shape similarity among 11 Megaluracarus species and two Dadayella species based on Mahalanobis distances computed from the canonical variate analysis. This UPGMA phenogram (unweighted-pair grouping method using averages) groups the nine character states discovered in the distribution patterns of ventroglandularia. Branches are labelled according to discrimination order defined by the canonical variates. Symbols in the plot and in the phenogram are as follows: solid green triangles, Arrenurus (Dadayella) adrianae; solid red rhombuses, Dadayella aztecus; lilac en-dashes, Arrenurus (Megaluracarus) anae; open blue circles, Megaluracarus anitahoffmannae; horizontal blue lines, Megaluracarus catoi; open red squares, Megaluracarus colitus; solid grey squares, Megaluracarus costeroae; open green rhombuses, Megaluracarus maya; solid black circles, Megaluracarus neoexpansus; blue asterisks, Megaluracarus olmeca; green hyphens, Megaluracarus tabascoensis; open pink triangles, Megaluracarus urbanus; purple plus signs, Megaluracarus zitavus.
Figure 3 in Geometric and traditional morphometrics for the assessment of character state identity: multivariate statistical analyses of character variation in the genus Arrenurus (Acari, Hydrachnidia, Arrenuridae)
Figure 3. Two Arrenurus (Dadayella) species included for comparison with the 11 species of Arrenurus (Megaluracarus) in the morphometric analyses: (A, B) Dadayella adrianae in dorsal and posterior view, respectively; (C, D) Dadayella aztecus in dorsal and posterior view, respectively. The arrows in (C) and (D) are as described in Figs 1F and 2F, respectively. Scale bars: 100 µm.
Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning: Summary statistics
<p>Summary statistics for a genome-wide association study (GWAS) of Alzheimer's disease CSF biomarkers principal components (PCs). This dataset accompanies the publication "Multivariate GWAS of Alzheimer’s disease CSF biomarker profiles implies GRIN2D in synaptic functioning". The article is currently in press at Genome Medicine. A link will be provided upon publication, but see the medRxiv preprint in the meantime:</p> <p>Neumann, A., Ohlei, O., Küçükali, F., Bos, I. J., Vos, S., Prokopenko, D., ... & Kristel Sleegers & Lars Bertram. (2022). Multivariate GWAS of Alzheimer’s disease CSF biomarker profiles implies GRIN2D in synaptic functioning. <em>medRxiv</em>, 2022-08. https://doi.org/10.1101/2022.08.02.22278185</p> <p>A GWAS was performed for five different PC biomarkers.</p> <p>PC1: Tau pathology/degeneration</p> <p>PC2: Aβ Pathology</p> <p>PC3: Injury/inflammation</p> <p>PC4: Non-AD inflammation</p> <p>PC5: Non-AD synaptic functioning</p> <p>Each GWAS was performed in either males and females ("all"), in females only ("female"), or in males only ("male"). In addition, we also ran an interaction model with sex as moderator ("interaction"). Each file includes output of the meta-analysis between the EMIF-AD study and ADNI.</p> <p>The files contain following columns:</p> <p>CHROM: Chromosome</p> <p>POS: Position according to Build 37</p> <p>ID: Chromosome:Position</p> <p>A1: Effect allele</p> <p>A2: Other allele</p> <p>BETA: Effect of one copy of the effect allele on biomarker PCs in SD. In case of sex interaction, the effect specific to females.</p> <p>SE: Standard Error</p> <p>P: p-value</p> <p>D: Direction in ADNI and EMIF-AD respectively</p> <p>Het: Heterogeneity statistics (I<sup>2</sup>, and corresponding χ<sup>2</sup>, degrees of freedom and p-value)</p>
Supplementary material for Roca-Neyra Equids: Late Miocene to Early Pleistocene Hipparion - Equus database for multivariate and statistical analysis for European fossil Equids
<p>We undertake a redescription of the equid sample from the early Pleistocene of Roca – Neyra, France. This locality has been recently calibrated at the Pliocene/Pleistocene boundary (2.6 ± 0.2 Ma) and therefore it is of interest for the first appearance of the genus <i>Equus </i>and last appearance of hipparionine horses. The Roca – Neyra equid sample, re – analyzed herein using morphological, morphometrical and statistical analyses, has revealed the co – occurrence of <i>Plesiohipparion</i> cf. ?<i>P.</i> <i>rocinantis</i> and <i>Equus</i> cf.<i> E. livenzovensis</i>. The analysis undertaken on several European, African and Asian <i>"Hipparion"</i> sensu lato species from late Miocene to early Pleistocene has revealed different remnant <i>Hipparion</i> lineages in the Plio – Pleistocene of Europe: <i>Plesiohipparion</i>, <i>Proboscidippaion</i> and likely <i>Cremohipparion</i>. The discovery of the first European monodactyl horse, <i>Equus</i> cf. <i>E.</i> <i>livenzovensis</i> in itself correlates Roca – Neyra with other 2.6 Ma European localities in Italy, Spain and in the Khapry area (Azov Sea region). The morphological description of the <i>Equus</i> cf. <i>E. livenzovensis</i> lower cheek teeth has highlighted intermediate features between the North American Pliocene species <i>Equus simplicidens</i> and early Pleistocene European <i>Equus stenonis.</i> Our study supports the hypothesis that <i>E. livenzovensis</i> is a plausible evolutionary predecessor for the <i>Equus stenonis</i> group. These observations underscore the importance of Roca – Neyra, as an important locality for the last European hipparions and the first <i>Equus</i> in the early Pleistocene of Europe.</p>
Data from: A generalized K statistic for estimating phylogenetic signal from shape and other high-dimensional multivariate data
Phylogenetic signal is the tendency for closely related species to display similar trait values due to their common ancestry. Several methods have been developed for quantifying phylogenetic signal in univariate traits and for sets of traits treated simultaneously, and the statistical properties of these approaches have been extensively studied. However, methods for assessing phylogenetic signal in high-dimensional multivariate traits like shape are less well developed, and their statistical performance is not well characterized. In this article, I describe a generalization of the K statistic of Blomberg et al. (2003) that is useful for quantifying and evaluating phylogenetic signal in highly-dimensional multivariate data. The method (Kmult) is found from the equivalency between statistical methods based on covariance matrices and those based on distance matrices. Using computer simulations based on Brownian motion, I demonstrate that the expected value of Kmult remains at 1.0 as trait variation among species is increased or decreased, and as the number of trait dimensions is increased. By contrast, estimates of phylogenetic signal found with a squared-change parsimony procedure for multivariate data change with increasing trait variation among species and with increasing numbers of trait dimensions, confounding biological interpretations. I also evaluate the statistical performance of hypothesis testing procedures based on Kmult and find that the method displays appropriate Type I error and high statistical power for detecting phylogenetic signal in high-dimensional data. Statistical properties of Kmult were consistent for simulations using bifurcating and random phylogenies, for simulations using different numbers of species, for simulations that varied the number of trait dimensions, and for different underlying models of trait covariance structure. Overall these findings demonstrate that Kmult provides a useful means of evaluating phylogenetic signal in high-dimensional multivariate traits. Finally, I illustrate the utility of the new approach by evaluating the strength of phylogenetic signal for head shape in a lineage of Plethodon salamanders.
Data from: A generalized K statistic for estimating phylogenetic signal from shape and other high-dimensional multivariate data
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