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Plink
PLINK is a free, commonly used, open-source whole-genome association analysis toolset designed by Shaun Purcell. The software is designed flexibly to perform a wide range of basic, large-scale genetic analyses. PLINK currently supports following functionalities: * data management; * basic statistics ( FST, missing data, tests of Hardy–Weinberg equilibrium, inbreeding coefficient, etc.); * Linkage disequilibrium (LD) calculation; * Identity by descent (IBD) and identity by state (IBS) matrix calculation; * population stratification, such as a Principal component analysis; * association analysis such as genome-wide association study for both basic case/control studies and quantitative traits; *tests for epistasis Epistasis is a phenomenon in genetics in which the effect of a gene mutation is dependent on the presence or absence of mutations in one or more other genes, respectively termed modifier genes. In other words, the effect of the mutation is depe ... Input and ou ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Whole Genome Association Study
In genomics, a genome-wide association study (GWA study, or GWAS), is an observational study of a genome-wide set of genetic variants in different individuals to see if any variant is associated with a trait. GWA studies typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits like major human diseases, but can equally be applied to any other genetic variants and any other organisms. When applied to human data, GWA studies compare the DNA of participants having varying phenotypes for a particular trait or disease. These participants may be people with a disease (cases) and similar people without the disease (controls), or they may be people with different phenotypes for a particular trait, for example blood pressure. This approach is known as phenotype-first, in which the participants are classified first by their clinical manifestation(s), as opposed to genotype-first. Each person gives a sample of DNA, from which millions of genetic variant ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Shaun Purcell
Shaun M. Purcell is a British genetic epidemiologist and statistical geneticist. He is a senior associate member of the Broad Institute of MIT and Harvard and its Stanley Center for Psychiatric Research. He is also a faculty member at the Brigham and Women's Hospital Department of Psychiatry. Having studied psychology and statistics at Oxford University, Purcell overcame the death of his supervisor David Fulker one year into a behavioural genetics programme at the Institute of Psychiatry to complete his Ph.D. under Pak Sham. He developed the PLINK genetics software during postdoctoral work with Mark Daly at the Whitehead Institute. He is also known for his research on the genetic bases of mental disorders such as schizophrenia and bipolar disorder, largely undertaken during faculty appointments at Massachusetts General Hospital and Mount Sinai in Manhattan Manhattan ( ) is the most densely populated and geographically smallest of the Boroughs of New York City, five borou ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fixation Index
The fixation index (FST) is a measure of population differentiation due to genetic structure. It is frequently estimated from Polymorphism (biology), genetic polymorphism data, such as single-nucleotide polymorphisms (SNP) or Microsatellite (genetics), microsatellites. Developed as a special case of Sewall WWright's F-statistics, it is one of the most commonly used statistics in population genetics. Its values range from 0 to 1, with 0 being no differentiation and 1 being complete differentiation. Interpretation This comparison of genetic variability within and between populations is frequently used in applied population genetics. The values range from 0 to 1. A zero value implies complete panmixia; that is, that the two populations are interbreeding freely. A value of one implies that all genetic variation is explained by the population structure, and that the two populations do not share any genetic diversity. For idealized models such as Isolation_by_distance#Sewall_Wright-_Ec ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Inbreeding Coefficient
The coefficient of relationship is a measure of the degree of consanguinity (or biological relationship) between two individuals. The term coefficient of relationship was defined by Sewall Wright in 1922, and was derived from his definition of the coefficient of inbreeding of 1921. The measure is most commonly used in genetics and genealogy. A coefficient of inbreeding can be calculated for an individual, and is typically one-half the coefficient of relationship between the parents. In general, the higher the level of inbreeding the closer the coefficient of relationship between the parents approaches a value of 1, expressed as a percentage, and approaches a value of 0 for individuals with arbitrarily remote common ancestors. Coefficient of relationship The coefficient of relationship r between two people B and C is obtained by a summation of coefficients calculated for every line by which they are connected to their common ancestors. Each such line connects the two peopl ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linkage Disequilibrium
Linkage disequilibrium, often abbreviated to LD, is a term in population genetics referring to the association of genes, usually linked genes, in a population. It has become an important tool in medical genetics and other fields In defining LD, it is important first to distinguish the two very different concepts, linkage disequilibrium and linkage (genetic linkage). Linkage disequilibrium refers to the association of genes ''in a population.'' Linkage, on the other hand, tells us whether genes are on the same chromosome ''in an individual''. There is no necessary relationship between the two. Genes that are closely linked may or may not be associated in populations. Looking at parents and offspring, if genes at closely linked loci are together in the parent then they will usually be together in the offspring. But looking at individuals in a population with no known common ancestry, it is much more difficult to see any relationships. To give a concrete, although imaginary, example i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Identity By Descent
A DNA segment is identical by descent (IBD) in two or more individuals if: * they have inherited it from a common ancestor without recombination, that is, the segment has the same ancestral origin in these individuals * the segment is maximal, that is, it is delimited at both ends by ancestral recombination events. Theory All individuals in a finite population are related if traced back long enough and will, therefore, share segments of their genomes IBD. During meiosis segments of IBD are broken up by recombination. Therefore, the expected length of an IBD segment depends on the number of generations since the most recent common ancestor at the locus of the segment. The length of IBD segments that result from a common ancestor ''n'' generations in the past (therefore involving 2''n'' meiosis) is exponentially distributed with mean 1/(2''n'') Morgans (M). The expected number of IBD segments decreases as the number of generations since the common ancestor at this locus incr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Population Stratification
Population structure (also called genetic structure and population stratification) is the presence of a systematic difference in allele frequencies between subpopulations. In a randomly mating (or ''panmictic'') population, allele frequencies are expected to be roughly similar between groups. However, mating tends to be non-random to some degree, causing structure to arise. For example, a barrier like a river can separate two groups of the same species and make it difficult for potential mates to cross; if a mutation occurs, over many generations it can spread and become common in one subpopulation while being completely absent in the other. Genetic variants do not necessarily cause observable changes in organisms, but can be correlated by coincidence because of population structure—a variant that is common in a population that has a high rate of disease may erroneously be thought to cause the disease. For this reason, population structure is a common confounding variable in m ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Principal Component Analysis
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified. The principal components of a collection of points in a real coordinate space are a sequence of p unit vectors, where the i-th vector is the direction of a line that best fits the data while being orthogonal to the first i-1 vectors. Here, a best-fitting line is defined as one that minimizes the average squared perpendicular distance from the points to the line. These directions (i.e., principal components) constitute an orthonormal basis in which different individual dimensions of the data are linearly uncorrelated. Many studies use the first two principal components in order to plot the data in two dimensions and to visually identi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Genome-wide Association Study
In genomics, a genome-wide association study (GWA study, or GWAS), is an observational study of a genome-wide set of Single-nucleotide polymorphism, genetic variants in different individuals to see if any variant is associated with a trait. GWA studies typically focus on associations between single-nucleotide polymorphisms (SNPs) and traits like major human diseases, but can equally be applied to any other genetic variants and any other organisms. When applied to human data, GWA studies compare the DNA of participants having varying phenotypes for a particular trait or disease. These participants may be people with a disease (cases) and similar people without the disease (controls), or they may be people with different phenotypes for a particular trait, for example blood pressure. This approach is known as phenotype-first, in which the participants are classified first by their clinical manifestation(s), as opposed to Genotype-first approach, genotype-first. Each person gives a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Epistasis
Epistasis is a phenomenon in genetics in which the effect of a gene mutation is dependent on the presence or absence of mutations in one or more other genes, respectively termed modifier genes. In other words, the effect of the mutation is dependent on the genetic background in which it appears. Epistatic mutations therefore have different effects on their own than when they occur together. Originally, the term ''epistasis'' specifically meant that the effect of a gene variant is masked by that of different gene. The concept of ''epistasis'' originated in genetics in 1907 but is now used in biochemistry, computational biology and evolutionary biology. The phenomenon arises due to interactions, either between genes (such as mutations also being needed in regulators of gene expression) or within them (multiple mutations being needed before the gene loses function), leading to non-linear effects. Epistasis has a great influence on the shape of evolutionary landscapes, which leads ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
