IMa2 For Windows [April-2022]
IMa2 is a Bayesian model-based analysis tool for inferring demographic history and related parameters of multiple populations. It uses an integrated set of C programs written in C++ and Java. IMa2 is also distributed as part of the MsBayes software package, which includes other Bayesian population genetic analyses tools such as BPP and the new IM program.
IMa2 supports historical population size and migration rate changes, admixture and migration between populations (no half-sib families required), random effects. It implements a variety of models such as the Infinite Island model, the stepping stone model and the mass-migration model. It supports a wide variety of demographic and genetic parameters such as effective population size (Ne), mutation, recombination, migration, mutation rates, migration rates, bottleneck size, sample sizes and distribution of the mutation effects (specifically, symmetric and asymmetric density models), among other things.
History
IMa was designed by Robert D. Nielsen in the mid-1990s. IMa, which stands for INtegrated MAlculator, was initially developed in 1995 and followed the methods of Ewens and Olsen and Hey. It was first published in 1996. IMa was open-sourced after the publications of the program arrived and the first version was released in November 2000, with the most recent release occurring in February 2017. IMa2 was first published in 2000, after the release of IMa, but was integrated into the MsBayes package in 2012.
The original release of IMa2 came in the form of a C++ program. In 2012, the program was moved to the MsBayes package. IMa2 now works with the original Open Source MsBayes and the online user interface MsBayes. In addition to the newer program, MsBayes is also distributed as a command line application. MsBayes is a much more recent and user friendly interface than the original IMa. It is also available for Linux and Windows.
References
External links
IMa2: Bayesian Estimation of Demographic and Migration History
Category:Genetics software
Category:Mathematical and quantitative methods (genetics)
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IMa2 Registration Code Free [2022]
Implementations
There are several implementations of IMa2 For Windows 10 Crack.
IMa2 Product Key_TUI: A command line interface to IMa2 2022 Crack
JBEAST: JBEAST is a Java implementation of IMa2
G-IM-1: This program implements the IMa2 and IMa2-mcmc algorithms in C or C++.
3.4: A program written in the Scipy language that implements IMa2 and IMa2-mcmc.
IMa2 extension
In addition to supporting IMa2, 3.4 implements a new extension to IMa2 called “IMa2-BL.” It is a version of IMa2 in which the M and Q parameters are used to make assumptions regarding the ancestral population size. In IMa2-BL, the parameter M is set to 0 (no reduction in the ancestral population size) and the parameter Q is set to a large value (1e10). This allows for scenarios in which the population size reduction was small (relative to the current population size) and likely occurred relatively recently in the past, before any of the sampled lineages have diverged. IMa2-BL is implemented in the JBEAST program.
References
Category:Population geneticsPages
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What’s New in the IMa2?
IMa2 was written by Peter F. Johansen, with significant assistance from Jos L. Hey and Ute Naumann. The program has been designed to fit very efficiently on 16-bit minis using DOS.
Example Usage
IMa2 can work on an individual data set, but for complex population genetics problems, its’ ability to create a variety of joint likelihoods (for example, for trios, simple binomial data, and non-uniform priors) allows it to be used in a number of ways. It can take a population covariance matrix and a hierarchical model, with the number of populations varying from 2 to 7. With a covariance matrix and a single population, it returns a joint likelihood function of the population parameters, for example, a joint likelihood of the allele frequencies.
The program was designed to provide the user with an easy way to perform likelihood analysis and Bayesian parameter estimation for complex population genetic models. IMa2 can analyze large data sets (for example, with human mtDNA sequences) and accept and analyze polyploid data. IMa2 provides the user with the ability to calculate joint likelihoods for multiple populations, and then jointly analyze the data in a Bayesian framework. IMa2 can be used to estimate different parameters across multiple populations at once, but also for a single population with complex model that includes up to four subpopulations. The program is very flexible and can be used with a variety of data types and for data sets of any size.
IMa2 can also handle data with multiple loci, and assign alleles and alleles to individuals. It implements a multivariate normal distribution with a covariance matrix, and a multinomial with a covariance matrix of the form covar(p) = qI(q>0). IMa2 uses this to perform the estimation of individual level subpopulation parameters, using the same random number generator as the standard IMa.
References
External links
Homepage of IMa2
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