Cophenetic Correlation Research Articles

THE USE OF GENETIC DISTANCE AND GROUPING METHODS TO PREDICT Eucalyptus Pellita F. MUELL GENITORS FOR HYBRIDIZATION

The objective of this study was to use quantitative traits to estimate the genetic distance among E. pellita provenances and progenies, to inform possible hybridization strategies in a species improvement program. A provenance and progeny test with 118 progenies from seven provenances was evaluated. The following quantitative traits were measured at seven years of age: diameter at breast height (DBH); height; and individual volume. The data were submitted to REML/BLUP analysis to obtain the predicted genetic value (BLUP). From this, the Mahalanobis (D²) genetic distance was estimated for provenances and progenies, which were then grouped by Tocher’s method, the unweighted pair group method using arithmetic averages (UPGMA), and principal component analysis (PCA). In total, 29 divergent groups were obtained among progenies based on Tocher’s method, which showed greater reliability according to the cophenetic correlation coefficient than UPGMA. The opposite was found between provenances, where the results for UPGMA demonstrated greater clustering reliability. Based on principal component analysis (PCA), the M. Ray and Tully provenances were the most similar, while Connl. A and Orchard were the most divergent. Height was the most important trait in estimating genetic distance. The results obtained offer important insights for breeding programs; with this information, crosses can be designed between contrasting individuals among and within provenances to obtain E. pellita hybrids, validating the possible heterotic groups identified through the genetic distance and grouping methods.

An improved agglomerative hierarchical clustering anomaly detection method for scientific data

SummaryAnomaly detection tries to find out the data that disobeys the rule of majority data or expected patterns. The traditional hierarchical clustering algorithms have been adopted to detect anomaly, but have the disadvantages of low effectiveness and unstability. So we propose an improved agglomerative hierarchical clustering method for anomaly detection. It dynamically adjusts the optimum clustering number according to the self‐defined criterion to save the trouble of manually picking clustering number, and determines the optimum clustering distance mode according to cophenetic correlation coefficient to reduce the procedure of manually testing the suitable distance mode in each iteration. The performances of proposed method are verified on tensile test, HTRU2 and credit card dataset. Compared with the traditional methods, our method possesses the most comprehensive performance (the highest F‐measure with less iterations), which shows effectiveness of anomaly detection. And compared with the traditional methods (single, complete, average, and centroid mode), our method achieves the best performance on tensile test and HTRU2 dataset, showing stronger generalization. Compared with other methods (Decision + Gradient Boosted Tree, Decision Trees + Decision Stump, etc) on credit card dataset, our method obtains similar accuracy, and ranks in the top level in the aspect of sensitivity.

Phenotypic Characterization of Tiger Nuts (Cyperus esculentus L.) from Major Growing Areas in Ghana.

Tigernut (Cyperus esculentus Lativum) is an important but understudied and underutilized crop in Ghana. The tubers are highly appreciated for their health benefits and nutritive value. To contribute to the conservation process of tiger nut and identify elite genotypes, this study was conducted to assess phenotypic variability in tiger nut genotypes in Ghana. Sixty-four (64) genotypes were collected from major tiger nut growing areas in Ghana. The genotypes were field-grown and characterized based on phenotypic and yield traits. Similarity coefficient (Bray-Curtis) was between 0.82 and 0.98, indicating low variability in both qualitative and quantitative characters. The cophenetic correlation coefficient was 0.64. The genotypes were mainly brown with only a few black (6) tubers from the central region. Materials collected from parts of the eastern region (Aduamoah) generally recorded the highest tuber weight. Tuber weight depended on plant height and number of tillers. There were high tillering genetic materials among the genotypes. Tubers were categorised as oval (10), ovoid (33), or oblong (15). The genotypes clustered into two groups based on shoot and tuber characteristics, rather than on geographical origin. The low genetic diversity among the genotypes suggested either the possible existence of a network among tiger nut farmers in Ghana in circulating the planting material or some form of seed sorting for uniform and homogenous planting materials has been carried out over the years. Our results point to the imperativeness to expand the genetic base of the tiger nuts to facilitate its improvement in Ghana.

Study of the Percentage of Greenhouse Gas Emissions from Aviation in the EU-27 Countries by Applying Multiple-Criteria Statistical Methods.

The transport sector, including air transport, represents an important source of air pollution. The present article deals with the current situation regarding greenhouse gas emissions in the air in 27 European Union (EU-27) member states. Every member state is characterized by selected parameters that determine the unique nature of a particular country (e.g., population, area, life expectancy, gross domestic product (GDP) per capita, etc.). In addition to these parameters, there were also other parameters which were monitored as they characterize the amount of greenhouse gas emissions and the impact of aviation on these emissions. The main purpose of the article is to compare the European Union member states on the basis of 15 examined parameters. The identification of similarities between the EU-27 member states with regard to the selected parameters was carried out by applying principal component analysis (PCA) and hierarchical cluster analysis. The average linkage method was applied to create a dendrogram representing the similarities between the examined member states. The value of the cophenetic correlation coefficient CC = 0.923 confirmed the correct application of the average linkage method. The cluster analysis outputs were five similarity-based homogeneous groups (clusters) into which the 27 member states were divided on the basis of the examined variables.

Similarity between Piaractus mesopotamicus, Colossoma macropomum and their interspecific hybrids

This study aimed to estimate the genetic similarities between Pacu (Piaractus mesopotamicus), Tambaqui (Colossoma macropomum) and their intraspecific hybrids. Sixty Pacu, Tambaqui, Tambacu and Paqui specimens were used, which were anaesthetised (benzocaine 60 mg/L), weighed and analysed for morphometric body parameters. Afterwards the animals were processed to obtain the weight and yield of viscera, head, fillet, ribs, skin and residue (backbone and fins). In order to carry out the clustering analysis the morphometric ratios, and weights and yields of the products and by-products obtained were determined. The Euclidean distances between groups were calculated based in the data collected, and the clustering methods Simple, Ward, Complete, Average, Median and Centroid were tested through cophenetic correlation. In general, all the clustering methods presented high cophenetic correlation (r > 0.70), with the lowest value by the Simple (0.7369) and the highest by the Average (0.7890) methods. In all dendrograms, similar fusion behaviour was observed, indicating a greater similarity between the Pacu and Paqui groups and between Tambaqui and Tambacu groups, only the metrics (maximum values) and the cut-off point varying between the different methods. The Average clustering method indicated a greater similarity of the hybrids with the species used as the female parent. Therefore, in a hybridisation strategy, it should be verified in which species, Pacu or Tambaqui, the characteristic of interest is best expressed before defining the maternal parent.

The Impact of Global Transcriptional Regulation on Bacterial Gene Order.

SummaryBacterial gene expression depends on the allocation of limited transcriptional resources provided a particular growth rate and growth condition. Early studies in a few genes suggested this global regulation to generate a unifying hyperbolic expression pattern. Here, we developed a large-scale method that generalizes these experiments to quantify the response to growth of over 700 genes that a priori do not exhibit any specific control. We distinguish a core subset following a promoter-specific hyperbolic response. Within this group, we sort genes with regard to their responsiveness to the global regulatory program to show that those with a particularly sensitive linear response are located near the origin of replication. We then find evidence that this genomic architecture is biologically significant by examining position conservation of E. coli genes in 100 bacteria. The response to the transcriptional resources of the cell results in an additional feature contributing to bacterial genome organization.

Composition and distribution of planktonic ciliates with indications to water quality in a shallow hypersaline lagoon (Pulicat Lake, India)

Planktonic ciliate composition and distribution together with physicochemical variables were investigated in a shallow hypersaline lagoon, Pulicat, India, during three seasons, i.e., pre-monsoon (PRM), monsoon (MON), and post-monsoon (POM). The low freshwater inflow, evaporation, and closure of the lake mouth were the main factors for the hypersaline conditions in Pulicat Lake. The average depth and salinity were 1.8 ± 0.12m (0.8 to 2.8m) and 35.3 ± 1.68 (12.5 to 61), respectively. A total of 29 ciliate taxa belonging to 18 genera and five classes were identified. Strombidium conicum (24%) was the dominant species followed by Euplotes sp. (10.7%) and Stenosomella sp. (7.02%). Spirotrichea (84%) was the dominant class followed by Oligohymenophorea (9.6%) and Heterotrichea (5.8%). Fabrea salina, a typical species in hypersaline systems, was abundant at locations where the salinity was more than 35. Multivariate analysis using the Bray-Curtis similarity, followed by SIMPROF (Similarity Percentage Analysis), on ciliate abundance data revealed three ciliate assemblages characterizing south, central, and north of the lake at 40% similarity (SIMPROF, cophenetic correlation = 0.622, P = 5%). Both ciliate abundance and chlorophyll-a were positively correlated with salinity. Species richness and evenness were higher in the south sector when compared with those in the other two sectors. Biotic-environmental interaction through canonical correspondence analysis (CCA) inferred that the combined effects of salinity, chlorophyll-a, and nutrient levels are the key factors responsible for the distribution of the ciliate species, suggesting that ciliates can be considered to be potential bioindicators of water quality.

A Data Mining Perspective of XRF Elemental Analysis from Pueblo People’s Pottery

Hierarchical clustering was used to identify elemental signatures in artifacts attributed to the Pueblo peoples. The artifacts in this study are pottery samples found at different sites in the state of New Mexico, USA. Three methods were applied: complete, average, and Ward. Their corresponding cophenetic correlation coefficients were used to contrast the three methods. Elemental characterization was only based on X-ray fluorescence excitation from a portable spectrometer with the silver anode. The elemental correlations here disclosed by data mining techniques are expected to guide further archaeological studies and assist experts in the assessment of provenance and historical ethnographic studies. XRF elemental analysis

Graph Similarity-based Hierarchical Clustering of Trajectory Data

Abstract Trajectory is the path traversed by any moving object like animals, human, vehicles and natural phenomenon. Trajectory analysis and clustering are essential to learn the dynamics of movement and pattern of moving objects. This paper proposes to cluster and identify similar trajectories based on paths traversed by moving object. The proposed algorithm has two phases graph generation and clustering. Moving objects generate a trace of GPS points which are converted into a graph, representing spatial regions. Graph generation methodology transforms trajectories into a series of spatial grid numbers and clustering algorithm group trajectories based on similarity measure which are calculated using edge and vertex similarity. Hierarchical clustering is done using graph based similar measures and the resulting clusters are validated using three measures namely Cophenetic Correlation Coefficient, Davies Bouldin Index and Dunn Index. Experimental analysis demonstrates the effectiveness in representation and clustering of trajectories based on graph model.

Genetic Diversity of Bertholletia excelsa Bonpl.: A Native Species of the Amazon Rainforest

Abstract In view of the economic and environmental importance of Bertholletia excelsa Bonpl. for the Amazon and the reducing natural habitat area of this species, the present study proposes to examine genetic variability among accessions of Brazil nut from the Amazon rainforest. Seventeen native Brazil nut genotypes were sampled from Sinop-MT and the genomic DNA were amplified using 15 inter-simple sequence repeat (ISSR) markers. The percent polymorphism and the polymorphism information content (PIC) of each primer were determined. The primers amplified 84.62% of the polymorphic bands and 15.38% of the monomorphic bands. The PIC for each primer ranged from 0 to 0.68. The Unweighted Pair Group Method with Arithmetic Mean (UPGMA) was the most efficient in group representation, as it showed the highest cophenetic correlation coefficient (CCC = 0.92), the lowest stress (12.31%) and the lowest distortion (1.51%). The use of ISSR markers was an efficient tool in the study of genetic diversity among Brazil nut genotypes, and the genetic diversity found can be used for conservation and pre-breeding programs for this crop.

Genetic Diversity of some Daffodil (Narcissus L. spp.) Genotypes in Turkey by Using SRAP Markers

Daffodil (Narcissus L. spp.) is one of the oldest ornamental flowers that have been cultivated from ancient times to nowadays. The species Narcissus tazetta L. and N. serotinus L. have spread out in different regions of Turkey and some other species have been naturalized. The purpose of this study was to characterize some daffodil populations that were collected from different regions of Turkey by using SRAP markers. Twenty-two daffodil populations of different species such as N. tazetta, N. serotinus, N. pseudonarcissus L., N. poeticus L. and N. jonquilla L. were used. Thirty-seven of 48 SRAP primer combinations showed scorable and polymorphic bands between samples. The similarity coefficients were used to construct a dendrogram by Unweighted Pair-Group Method with Arithmetic Averages (UPGMA) using NTSYS-PC. Cophenetic correlation between ultrametric similarities of tree and similarity matrix were high (r = 0.97). The genotypes of Narcissus species were divided into 2 main groups. Although there was less genetic variation among N. tazetta species, even collected from different regions of Turkey, N. poeticus, N. pseudonarsis, N. jonquilla and N. serotinus had more genetic divergence among them. It can be concluded that genetic variation of Narcissus species can be used for daffodil breeding programs.
 
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 In press - Online First. Article has been peer reviewed, accepted for publication and published online without pagination. It will receive pagination when the issue will be ready for publishing as a complete number (Volume 47, Issue 4, 2019). The article is searchable and citable by Digital Object Identifier (DOI). DOI link will become active after the article will be included in the complete issue.
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ANALISIS KLASTER METODE WARD DAN AVERAGE LINKAGE DENGAN VALIDASI DUNN INDEX DAN KOEFISIEN KORELASI COPHENETIC (Studi Kasus: Kecelakaan Lalu Lintas Berdasarkan Jenis Kendaraan Tiap Kabupaten/Kota di Jawa Tengah Tahun 2018)

Based on Central Java Regional Police data, traffic accidents from 2017 to 2018 increased from 17.522 to 19.016 or 8,54 percent. To reduce the number of traffic accidents in Central Java, the initial step was carried out by grouping districts/cities that had the same accident level characteristics based on vehicle type with cluster analysis. The ward and average linkage method is a hierarchical cluster analysis method. ward method can maximize cluster homogeneity. While the average linkage method can generate clusters with small cluster variants. In this study using a measure of squared euclidean distance to measure the similarity between pairs of objects. To determine the quality of clustering results, the validation dunn index and cophenetic coefficients corelation are used. Based on the results of the clustering, the optimal number of clusters is obtained at q = 5 for the average linkage method with the results of validation dunn index = 0,08571196 and the rcoph = 0,687458. Keywords: Accidents, Cluster Analysis, Ward Method, Average linkage, Squared Euclidean Distance, Dunn Index, Cophenetic Correlation Coefficient

Evaluation of data analytics based clustering algorithms for knowledge mining in a student engagement data

The application of algorithms based on data analytics for the task of knowledge mining in a student dataset is an important strategy for improving learning outcomes, student success and supporting strategic decision making in higher educa�tional institutions of learning. However, the widely used data analytics based clustering algorithms are highly data dependent, making it pertinent to find the most effective algorithm for knowledge mining in a dataset associated with student engage�ment. In this study, performances of five famous clustering algorithms are evaluated for this purpose. The k-means algorithm was benchmarked with 22 distance functions based on the Silhouette index, Dunn’s index and partition entropy internal valid�ity metrics. The hierarchical clustering algorithm was benchmarked with the Cophenetic correlation coefficient computed for different combinations of distance and linkage functions. The Fuzzy c-means algorithm was benchmarked with the partition entropy, partition coefficient, Silhouette index and modified partition coefficient. The k-nearest neighbor algorithm was applied to determine the optimum epsilon value for the density-based spatial clustering of applications with noise. The default param�eter settings were accepted for the expectation-maximization algorithm. The overall ranking of the clustering algorithms was based on cluster potentiality using the median deviation statistics. The results of the evaluation show the well-known k-means algorithm to have the highest cluster potentiality, demonstrating its effectiveness for the task of knowledge mining in a student engagement dataset

Associations between pigments, antioxidant activity and coloring of blackberry fruits (Rubus sp.) and jellies through storage

The objective of this study was to investigate the relations between the amount of anthocyanins, carotenoids and the antioxidant activity measured by the FRAP and TEAC methods. Furthermore, pigments and the coloration of blackberry harvested fruits were measured at 3 different collection points then fruits stored in refrigerated environment and the jelly made from them, preserved in hermetically sealed glasses, without contact with light and temperature of 25ºC. In order to investigate the relations between the study variables (content of anthocyanins and carotenoids, antioxidant activity and coloration using digital colorimeter), Pearson’s correlation analysis was adopted, which indicates the existence of a positive or negative relation between two variables. The α = 5% (correlation coefficient) was used to verify the significance of the correlation. The Mahalanobis (D2) generalized distance for the clustering analysis by the mean linkage method between group of blackberry fruits and jellies was applied. Furthermore, the cophenetic correlation coefficient and multivariate analysis using major components were applied to verify the grouping of different responses of harvesting points of fresh blackberry fruit in natura and jellies. The results showed that there was correlation between the content of anthocyanins and carotenoids in fruits (0.99*) and between the same parameters in jellies. However, this behavior was not clearly observed between the pigments and the antioxidant activity. There was a positive correlation between the factors involved in the coloring of chroma fruits ‘L’, ‘a’, ‘b’ and ºHue in fruits and jellies. Blackberry jellies presented as good sources of anthocyanins and carotenoids.

Screening of Chilli ( Capsicum annum L.) Genotypes for Drought Tolerant at Seedling Emergence Stage

Forty seven chilli (Capsicum annum L.) genotypes were evaluated for their genetic potential to drought tolerant at germination stage using 12.5% polyethylene (PEG, MW6000). Relative germination energy (RGE), relative germination rate (RGR), relative germination index (RGI), relative vitality index (RVI) and their relative PEG injury rate were computed to identify the most tolerant genotypes on germination stage. Significant differences were observed among the genotypes, treatments and their interactions for evaluated traits suggesting a great amount of variability for drought tolerant in chilli. Based on aggregated score of RGE, RGR, RGI and RVI parameters BD-10906, BD-10912, BD-10911, BD-10916 and BD-10913 were the top five genotypes, whereas BD-10902, RT-20, AM-29, BD-10893 and BD-10930 lowermost five genotypes in the rank of drought tolerant which is an indication of their tolerant and susceptible to drought stress. The lowest relative PEG injury rate was observed in tolerant genotypes, contrary the highest rate was recorded in susceptible genotypes. Dendrogram using Agglomerative Clustering Method grouped the 47 genotypes into four different clusters at the 0.668 co-phenetic correlation coefficient. Drought tolerant chilli genotypes grouped in cluster I, while the susceptible genotypes clustered together in group III and IV and a number of moderate tolerant genotypes gathered in cluster II. Consequently the maximum mean values of tested parameters viz. RGR (91.30), RGE (30.43), RGI (40.58) and RVI (54.10) were observed in clusters I. Positive and significant correlation values were observed between the tolerant indications parameters. RGI showed comparatively strong and positive correlation with all tested parameters. Thus, tolerant and susceptible genotypes will be progressed for further tolerant study in seedling stage.

Versatile Linkage: a Family of Space-Conserving Strategies for Agglomerative Hierarchical Clustering

Agglomerative hierarchical clustering can be implemented with several strategies that differ in the way elements of a collection are grouped together to build a hierarchy of clusters. Here we introduce versatile linkage, a new infinite system of agglomerative hierarchical clustering strategies based on generalized means, which go from single linkage to complete linkage, passing through arithmetic average linkage and other clustering methods yet unexplored such as geometric linkage and harmonic linkage. We compare the different clustering strategies in terms of cophenetic correlation, mean absolute error, and also tree balance and space distortion, two new measures proposed to describe hierarchical trees. Unlike the $\beta$-flexible clustering system, we show that the versatile linkage family is space-conserving.

COMPARATION OF DENDROGRAM AND CLADOGRAM TOPOLOGY OF Gyrinops versteegii AND OTHERS GYRINOPS MEMBER FOR POLYPHASIC TAXONOMY

The purpose of this research is to compare topology of dendrogram and cladogram of G. versteegii and others Gyrinops members for polyphasic taxonomy approach. Character of leaf, stem, flower and fruit of Gyrinops member were used for numeric phenetic analysis. On the other hands, trnL-trnF interspacer of chloroplast gene sequence were used for phylogenetic analysis. MVSP 3.1A were used for dendrogram construction using Simple Matching Coefficient and Jaccard’s Coefficient as clustering method. Co-stat cohor 6 were used for cophenetic correlation analysis. Multiple sequence alignment of trnL – trnF was carried by ClustalX 2.1 program. MEGA program was used for reconstruction of cladogram. This cladogram uses two different approach algorithms including: Neighbor Joining and Maximum Likelihood with 1000 bootstrap replication. Sequences similarity matrix analysis were carried by Phydit program with cut off value 99% for each Gyrinops members. Based on result, simple matching dendrogram has the same topology as Jaccard’s dendrogram. Cophenetic correlation analysis also confirm that there is no distortion on clustering analysis of these two dendrograms. On the other hand, Neighbor Joining cladogram has different topology from Maximum Likelihood cladogram. Similarity analysis of trnL-trnF sequence shows that each member of Gyrinops has strong phylogenetic relationship. Comparation of dendrogram and cladogram of G. versteegii with other Gyrinops members confirm that this species has different clustering group on dendrogram and cladogram. It could be concluded that G. versteegii has unique phylogenetic relationship and similarity relationship with others Gyrinops members.

PID: a PDF-induced distance based on permutation cross-distribution entropy

In this paper, a PDF-induced distance (PID) based on permutation cross-distribution entropy is proposed to measure the dissimilarity between complex time series. It overcomes the effects of spatial distance by focusing on similar local fluctuation patterns. It also corrects the disadvantage of being insensitive to symmetric skewness distributions. We have applied PID to synthetic data and financial time series. The Euclidean distance is employed as a reference. In simulated experiments, eight signals generated from four models are detected, and results are presented by hierarchical clustering analysis via PID, which is correctly clustered and superior to other methods. Then, PID is applied to the real-world financial time series. Eight stocks in the global financial markets are employed. It reveals that they are clearly divided based on their financial backgrounds. The cophenetic correlation coefficient is used to measure the quality of solutions. It reveals that the PID is convincing and superior to the Euclidean distance. In addition, as a classic method for non-stationary time series, detrended cross-correlation analysis (DCCA) is adopted to compare the superiority of PID. Although experiments show that DCCA does perform well, it is inferior to PID. Also, we conduct additional experiments on the effects of non-Gaussian noises. Excitingly, PID can still cluster signals accurately after adding uniformly distributed noises, and the cophenetic correlation coefficient reaches 0.9788.

A new agglomerative hierarchical clustering to model student activity in online learning

In this paper, a new technique of agglomerative hierarchical clustering (AHC), which is known as SLG (single linkage dissimilarity increment distribution, global cumulative score standard), can work well in analyzing students' activity in online learning as evidenced by obtaining the highest score in testing the validity index of cophenetic correlation coefficient (CPCC) ie 0.9237, 0.9015, 0.9967, 0.8853, 0.9875 of the five datasets compared with conventional agglomerative hierarchical clustering methods.

Combinations of distance measures and clustering algorithms in pepper germplasm characterization

ABSTRACT Characterization and evaluation of genotypes conserved in the germplasm banks have become of great importance due to gradual loss of genetic variability and search for more adapted and productive genotypes. This can be obtained through several ways, generating quantitative and qualitative data. Joint analysis of those variables may be considered a strategy for an accurate germplasm characterization. In this study we aimed to evaluate different clustering techniques for characterization and evaluation of Capsicum spp. accessions using combinations of specific measures for quantitative and qualitative variables. A collection of 56 Capsicum spp. accessions was characterized based on 25 morphoagronomic descriptors. Six quantitative distances were used [A1) average of the range-standardized absolute difference (Gower), A2) Pearson correlation, A3) Kulczynski, A4) Canberra, A5) Bray-Curtis, and A6) Morisita] combined with distance for qualitative data [Simple Coincidence (B1)]. Clustering analyses were performed using agglomerative hierarchical methods (Ward, the nearest neighbor, the farthest neighbor, UPGMA and WPGMA). All combined distances were highly correlated. UPGMA clustering was the most efficient through cophenetic correlation and 2-norm analyses, showing a concordance between the two methods. Six clusters were considered an ideal number by UPGMA clustering, in which Gower distance showed a better adjustment for clustering. Most combined distances using UPGMA clustering allowed the separation of the accessions in relation to species, using both quantitative and qualitative data, which could be an alternative for simultaneous joint analysis, aiming to compare different clusters.