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Dendrograms
A dendrogram is a diagram representing a tree graph. This diagrammatic representation is frequently used in different contexts: * in hierarchical clustering, it illustrates the arrangement of the clusters produced by the corresponding analyses. * in computational biology, it shows the clustering of genes or samples, sometimes in the margins of heatmaps. * in phylogenetics, it displays the evolutionary relationships among various biological taxa. In this case, the dendrogram is also called a phylogenetic tree. The name ''dendrogram'' derives from the two ancient greek words (), meaning "tree", and (), meaning "drawing, mathematical figure". Clustering example For a clustering example, suppose that five taxa (a to e) have been clustered by UPGMA based on a matrix of genetic distances. The hierarchical clustering dendrogram would show a column of five nodes representing the initial data (here individual taxa), and the remaining nodes represent the clusters to whic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hierarchical Clustering
In data mining and statistics, hierarchical clustering (also called hierarchical cluster analysis or HCA) is a method of cluster analysis that seeks to build a hierarchy of clusters. Strategies for hierarchical clustering generally fall into two categories: * Agglomerative: Agglomerative: Agglomerative clustering, often referred to as a "bottom-up" approach, begins with each data point as an individual cluster. At each step, the algorithm merges the two most similar clusters based on a chosen distance metric (e.g., Euclidean distance) and linkage criterion (e.g., single-linkage, complete-linkage). This process continues until all data points are combined into a single cluster or a stopping criterion is met. Agglomerative methods are more commonly used due to their simplicity and computational efficiency for small to medium-sized datasets . * Divisive: Divisive clustering, known as a "top-down" approach, starts with all data points in a single cluster and recursively splits the clu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
UPGMA Dendrogram Hierarchical
UPGMA (unweighted pair group method with arithmetic mean) is a simple agglomerative (bottom-up) hierarchical clustering method. It also has a weighted variant, WPGMA, and they are generally attributed to Robert R. Sokal, Sokal and Charles Duncan Michener, Michener. Note that the unweighted term indicates that all distances contribute equally to each average that is computed and does not refer to the math by which it is achieved. Thus the simple averaging in WPGMA produces a weighted result and the proportional averaging in UPGMA produces an unweighted result (''#Second_distance_matrix_update, see the working example''). Algorithm The UPGMA algorithm constructs a rooted tree (dendrogram) that reflects the structure present in a pairwise similarity matrix (or a distance matrix, dissimilarity matrix). At each step, the nearest two clusters are combined into a higher-level cluster. The distance between any two clusters \mathcal and \mathcal, each of size (''i.e.'', cardinality) and , ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
UPGMA
UPGMA (unweighted pair group method with arithmetic mean) is a simple agglomerative (bottom-up) hierarchical clustering method. It also has a weighted variant, WPGMA, and they are generally attributed to Sokal and Michener. Note that the unweighted term indicates that all distances contribute equally to each average that is computed and does not refer to the math by which it is achieved. Thus the simple averaging in WPGMA produces a weighted result and the proportional averaging in UPGMA produces an unweighted result ('' see the working example''). Algorithm The UPGMA algorithm constructs a rooted tree ( dendrogram) that reflects the structure present in a pairwise similarity matrix (or a dissimilarity matrix). At each step, the nearest two clusters are combined into a higher-level cluster. The distance between any two clusters \mathcal and \mathcal, each of size (''i.e.'', cardinality) and , is taken to be the average of all distances d(x,y) between pairs of objects x in \m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Heatmap RNAseqV2 1
A heat map (or heatmap) is a 2-dimensional data visualization technique that represents the magnitude of individual values within a dataset as a color. The variation in color may be by hue or intensity. In some applications such as crime analytics or website click-tracking, color is used to represent the ''density'' of data points rather than a value associated with each point. "Heat map" is a relatively new term, but the practice of shading matrices has existed for over a century. History Heat maps originated in 2D displays of the values in a data matrix. Larger values were represented by small dark gray or black squares (pixels) and smaller values by lighter squares. The earliest known example dates to 1873, when Toussaint Loua used a hand-drawn and colored shaded matrix to visualize social statistics across the districts of Paris. The idea of reordering rows and columns to reveal structure in a data matrix, known as seriation, was introduced by Flinders Petrie in 1899. In ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Heat Map
A heat map (or heatmap) is a 2-dimensional data visualization technique that represents the magnitude of individual values within a dataset as a color. The variation in color may be by hue or intensity. In some applications such as crime analytics or website click-tracking, color is used to represent the ''density'' of data points rather than a value associated with each point. "Heat map" is a relatively new term, but the practice of shading matrices has existed for over a century. History Heat maps originated in 2D displays of the values in a data matrix. Larger values were represented by small dark gray or black squares (pixels) and smaller values by lighter squares. The earliest known example dates to 1873, when Toussaint Loua used a hand-drawn and colored shaded matrix to visualize social statistics across the districts of Paris. The idea of reordering rows and columns to reveal structure in a data matrix, known as seriation, was introduced by Flinders Petrie in 1899. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Statistical Charts And Diagrams
Statistics (from German: ', "description of a state, a country") is the discipline that concerns the collection, organization, analysis, interpretation, and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of surveys and experiments. When census data (comprising every member of the target population) cannot be collected, statisticians collect data by developing specific experiment designs and survey samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample to the population as a whole. An experimental study involves taking measurements of the sy ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Trees (data Structures)
In botany, a tree is a perennial plant with an elongated stem, or trunk, usually supporting branches and leaves. In some usages, the definition of a tree may be narrower, e.g., including only woody plants with secondary growth, only plants that are usable as lumber, or only plants above a specified height. But wider definitions include taller palms, tree ferns, bananas, and bamboos. Trees are not a monophyletic taxonomic group but consist of a wide variety of plant species that have independently evolved a trunk and branches as a way to tower above other plants to compete for sunlight. The majority of tree species are angiosperms or hardwoods; of the rest, many are gymnosperms or softwoods. Trees tend to be long-lived, some trees reaching several thousand years old. Trees evolved around 400 million years ago, and it is estimated that there are around three trillion mature trees in the world currently. A tree typically has many secondary branches supported clear ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
R (programming Language)
R is a programming language for statistical computing and Data and information visualization, data visualization. It has been widely adopted in the fields of data mining, bioinformatics, data analysis, and data science. The core R language is extended by a large number of R package, software packages, which contain Reusability, reusable code, documentation, and sample data. Some of the most popular R packages are in the tidyverse collection, which enhances functionality for visualizing, transforming, and modelling data, as well as improves the ease of programming (according to the authors and users). R is free and open-source software distributed under the GNU General Public License. The language is implemented primarily in C (programming language), C, Fortran, and Self-hosting (compilers), R itself. Preprocessor, Precompiled executables are available for the major operating systems (including Linux, MacOS, and Microsoft Windows). Its core is an interpreted language with a na ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Taxonomy
image:Hierarchical clustering diagram.png, 280px, Generalized scheme of taxonomy Taxonomy is a practice and science concerned with classification or categorization. Typically, there are two parts to it: the development of an underlying scheme of classes (a taxonomy) and the allocation of things to the classes (classification). Originally, taxonomy referred only to the Taxonomy (biology), classification of organisms on the basis of shared characteristics. Today it also has a more general sense. It may refer to the classification of things or concepts, as well as to the principles underlying such work. Thus a taxonomy can be used to organize species, documents, videos or anything else. A taxonomy organizes taxonomic units known as "taxa" (singular "taxon"). Many are hierarchy, hierarchies. One function of a taxonomy is to help users more easily find what they are searching for. This may be effected in ways that include a library classification system and a Taxonomy for search e ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Freeware
Freeware is software, often proprietary, that is distributed at no monetary cost to the end user. There is no agreed-upon set of rights, license, or EULA that defines ''freeware'' unambiguously; every publisher defines its own rules for the freeware it offers. For instance, modification, redistribution by third parties, and reverse engineering are permitted by some publishers but prohibited by others. Unlike with free and open-source software, which are also often distributed free of charge, the source code for freeware is typically not made available. Freeware may be intended to benefit its producer by, for example, encouraging sales of a more capable version, as in the freemium and shareware business models. History The term ''freeware'' was coined in 1982 by Andrew Fluegelman, who wanted to sell PC-Talk, the communications application he had created, outside of commercial distribution channels. Fluegelman distributed the program via the same process as ''shareware''. As s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
MEGA, Molecular Evolutionary Genetics Analysis
Molecular Evolutionary Genetics Analysis (MEGA) is computer software for conducting statistical analysis of molecular evolution and for constructing phylogenetic trees. It includes many sophisticated methods and tools for phylogenomics and phylomedicine. It is licensed as proprietary freeware. The project for developing this software was initiated by the leadership of Masatoshi Nei in his laboratory at the Pennsylvania State University in collaboration with his graduate student Sudhir Kumar and postdoctoral fellow Koichiro Tamura.Kumar, S., K. Tamura, and M. Nei (1993) MEGA: Molecular Evolutionary Genetics Analysis. Ver. 1.0, The Pennsylvania State University, University Park, PA. Nei wrote a monograph (pp. 130) outlining the scope of the software and presenting new statistical methods that were included in MEGA. The entire set of computer programs was written by Kumar and Tamura. The personal computers then lacked the ability to send the monograph and software electronica ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
