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Bayesian Tool For Methylation Analysis
Bayesian tool for methylation analysis, also known as BATMAN, is a statistical tool for analysing methylated DNA immunoprecipitation (MeDIP) profiles. It can be applied to large datasets generated using either oligonucleotide arrays (MeDIP-chip) or next-generation sequencing (MeDIP-seq), providing a quantitative estimation of absolute methylation state in a region of interest. Theory MeDIP (methylated DNA immunoprecipitation) is an experimental technique used to assess DNA methylation levels by using an antibody to isolate methylated DNA sequences. The isolated fragments of DNA are either hybridized to a microarray chip (MeDIP-chip) or sequenced by next-generation sequencing (MeDIP-seq). While this tells you what areas of the genome are methylated, it does not give absolute methylation levels. Imagine two different genomic regions, ''A'' and ''B''. Region ''A'' has six CpGs (DNA methylation in mammalian somatic cells generally occurs at CpG dinucleotides), three of which are methyl ...
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Methylated DNA Immunoprecipitation
Methylated DNA immunoprecipitation (MeDIP or mDIP) is a large-scale (chromosome- or genome-wide) purification technique in molecular biology that is used to enrich for methylated DNA sequences. It consists of isolating methylated DNA fragments via an antibody raised against 5-methylcytosine (5mC). This technique was first described by Weber M. ''et al.'' in 2005 and has helped pave the way for viable methylome-level assessment efforts, as the purified fraction of methylated DNA can be input to high-throughput DNA detection methods such as high-resolution DNA microarrays ( MeDIP-chip) or next-generation sequencing (MeDIP-seq). Nonetheless, understanding of the methylome remains rudimentary; its study is complicated by the fact that, like other epigenetic properties, patterns vary from cell-type to cell-type. Background DNA methylation, referring to the reversible methylation of the 5 position of cytosine by methyltransferases, is a major epigenetic modification in multicellul ...
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Continuous Variable
In mathematics and statistics, a quantitative variable may be continuous or discrete if they are typically obtained by ''measuring'' or ''counting'', respectively. If it can take on two particular real values such that it can also take on all real values between them (even values that are arbitrarily close together), the variable is continuous in that interval. If it can take on a value such that there is a non-infinitesimal gap on each side of it containing no values that the variable can take on, then it is discrete around that value. In some contexts a variable can be discrete in some ranges of the number line and continuous in others. Continuous variable A continuous variable is a variable whose value is obtained by measuring, i.e., one which can take on an uncountable set of values. For example, a variable over a non-empty range of the real numbers is continuous, if it can take on any value in that range. The reason is that any range of real numbers between a and b wit ...
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Vertebrate
Vertebrates () comprise all animal taxa within the subphylum Vertebrata () ( chordates with backbones), including all mammals, birds, reptiles, amphibians, and fish. Vertebrates represent the overwhelming majority of the phylum Chordata, with currently about 69,963 species described. Vertebrates comprise such groups as the following: * jawless fish, which include hagfish and lampreys * jawed vertebrates, which include: ** cartilaginous fish (sharks, rays, and ratfish) ** bony vertebrates, which include: *** ray-fins (the majority of living bony fish) *** lobe-fins, which include: **** coelacanths and lungfish **** tetrapods (limbed vertebrates) Extant vertebrates range in size from the frog species ''Paedophryne amauensis'', at as little as , to the blue whale, at up to . Vertebrates make up less than five percent of all described animal species; the rest are invertebrates, which lack vertebral columns. The vertebrates traditionally include the hagfish, which do no ...
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Cancer
Cancer is a group of diseases involving abnormal cell growth with the potential to invade or spread to other parts of the body. These contrast with benign tumors, which do not spread. Possible signs and symptoms include a lump, abnormal bleeding, prolonged cough, unexplained weight loss, and a change in bowel movements. While these symptoms may indicate cancer, they can also have other causes. Over 100 types of cancers affect humans. Tobacco use is the cause of about 22% of cancer deaths. Another 10% are due to obesity, poor diet, lack of physical activity or excessive drinking of alcohol. Other factors include certain infections, exposure to ionizing radiation, and environmental pollutants. In the developing world, 15% of cancers are due to infections such as ''Helicobacter pylori'', hepatitis B, hepatitis C, human papillomavirus infection, Epstein–Barr virus and human immunodeficiency virus (HIV). These factors act, at least partly, by changing the genes of ...
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CNV Value
CNV may refer to: * Chinese New Version, a Chinese language Bible translation * Choroidal neovascularization in ophthalmology * City of North Vancouver in British Columbia, as opposed to its surrounding District of North Vancouver * Christelijk Nationaal Vakverbond in Dutch Trade Unions * Copy number variation in genetics *contingent negative variation in evoked potentials *Cranial nerve V In neuroanatomy, the trigeminal nerve ( lit. ''triplet'' nerve), also known as the fifth cranial nerve, cranial nerve V, or simply CN V, is a cranial nerve responsible for sensation in the face and motor functions such as biting and chewing; ..., also known as the trigeminal nerve * Communication Non Violente, the French version of the acronym NVC Non Violent Communication {{disambig ...
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Copy Number Variation
Copy number variation (CNV) is a phenomenon in which sections of the genome are repeated and the number of repeats in the genome varies between individuals. Copy number variation is a type of structural variation: specifically, it is a type of duplication or deletion event that affects a considerable number of base pairs. Approximately two-thirds of the entire human genome may be composed of repeats and 4.8–9.5% of the human genome can be classified as copy number variations. In mammals, copy number variations play an important role in generating necessary variation in the population as well as disease phenotype. Copy number variations can be generally categorized into two main groups: short repeats and long repeats. However, there are no clear boundaries between the two groups and the classification depends on the nature of the loci of interest. Short repeats include mainly dinucleotide repeats (two repeating nucleotides e.g. A-C-A-C-A-C...) and trinucleotide repeats. Long r ...
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Command-line Interface
A command-line interpreter or command-line processor uses a command-line interface (CLI) to receive commands from a user in the form of lines of text. This provides a means of setting parameters for the environment, invoking executables and providing information to them as to what actions they are to perform. In some cases the invocation is conditional based on conditions established by the user or previous executables. Such access was first provided by computer terminals starting in the mid-1960s. This provided an interactive environment not available with punched cards or other input methods. Today, many users rely upon graphical user interfaces and menu-driven interactions. However, some programming and maintenance tasks may not have a graphical user interface and use a command line. Alternatives to the command-line interface include text-based user interface menus (for example, IBM AIX SMIT), keyboard shortcuts, and various desktop metaphors centered on the pointer (usual ...
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Software
Software is a set of computer programs and associated documentation and data. This is in contrast to hardware, from which the system is built and which actually performs the work. At the lowest programming level, executable code consists of machine language instructions supported by an individual processor—typically a central processing unit (CPU) or a graphics processing unit (GPU). Machine language consists of groups of binary values signifying processor instructions that change the state of the computer from its preceding state. For example, an instruction may change the value stored in a particular storage location in the computer—an effect that is not directly observable to the user. An instruction may also invoke one of many input or output operations, for example displaying some text on a computer screen; causing state changes which should be visible to the user. The processor executes the instructions in the order they are provided, unless it is instructed ...
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Beta Distribution
In probability theory and statistics, the beta distribution is a family of continuous probability distributions defined on the interval , 1in terms of two positive parameters, denoted by ''alpha'' (''α'') and ''beta'' (''β''), that appear as exponents of the random variable and control the shape of the distribution. The beta distribution has been applied to model the behavior of random variables limited to intervals of finite length in a wide variety of disciplines. The beta distribution is a suitable model for the random behavior of percentages and proportions. In Bayesian inference, the beta distribution is the conjugate prior probability distribution for the Bernoulli, binomial, negative binomial and geometric distributions. The formulation of the beta distribution discussed here is also known as the beta distribution of the first kind, whereas ''beta distribution of the second kind'' is an alternative name for the beta prime distribution. The generalization to mult ...
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Nested Sampling
The nested sampling algorithm is a computational approach to the Bayesian statistics problems of comparing models and generating samples from posterior distributions. It was developed in 2004 by physicist John Skilling. Background Bayes' theorem can be applied to a pair of competing models M_1 and M_2 for data D, one of which may be true (though which one is unknown) but which both cannot be true simultaneously. The posterior probability for M_1 may be calculated as: : \begin P(M_1\mid D) & = \frac \\ & = \frac \\ & = \frac \end The prior probabilities M_1 and M_2 are already known, as they are chosen by the researcher ahead of time. However, the remaining Bayes factor P(D\mid M_2)/P(D\mid M_1) is not so easy to evaluate, since in general it requires marginalizing nuisance parameters. Generally, M_1 has a set of parameters that can be grouped together and called \theta, and M_2 has its own vector of parameters that may be of different dimensionality, but is still termed \ ...
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Bayesian Probability
Bayesian probability is an Probability interpretations, interpretation of the concept of probability, in which, instead of frequentist probability, frequency or propensity probability, propensity of some phenomenon, probability is interpreted as reasonable expectation representing a state of knowledge or as quantification of a personal belief. The Bayesian interpretation of probability can be seen as an extension of propositional logic that enables reasoning with Hypothesis, hypotheses; that is, with propositions whose truth value, truth or falsity is unknown. In the Bayesian view, a probability is assigned to a hypothesis, whereas under frequentist inference, a hypothesis is typically tested without being assigned a probability. Bayesian probability belongs to the category of evidential probabilities; to evaluate the probability of a hypothesis, the Bayesian probabilist specifies a prior probability. This, in turn, is then updated to a posterior probability in the light of new, re ...
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Probability Density Function
In probability theory, a probability density function (PDF), or density of a continuous random variable, is a function whose value at any given sample (or point) in the sample space (the set of possible values taken by the random variable) can be interpreted as providing a ''relative likelihood'' that the value of the random variable would be close to that sample. Probability density is the probability per unit length, in other words, while the ''absolute likelihood'' for a continuous random variable to take on any particular value is 0 (since there is an infinite set of possible values to begin with), the value of the PDF at two different samples can be used to infer, in any particular draw of the random variable, how much more likely it is that the random variable would be close to one sample compared to the other sample. In a more precise sense, the PDF is used to specify the probability of the random variable falling ''within a particular range of values'', as opposed to ...
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