What does PSMC mean in UNCLASSIFIED
The Pairwise Sequentially Markovian Coalescent (PSMC) is an advanced method of genetic population inferring. It was developed to calculate the demographic history of a species or population based on its genetic information. The PSMC method examines the differences in allele frequency over time between two distinct sets of individuals at any given period, and from that data can estimate the likely changes in their underlying population size and structure. This method has been used to analyze the evolutionary histories of many organisms, including humans, primates, rodents and bacteria.
PSMC meaning in Unclassified in Miscellaneous
PSMC mostly used in an acronym Unclassified in Category Miscellaneous that means pairwise sequentially Markovian coalescent
Shorthand: PSMC,
Full Form: pairwise sequentially Markovian coalescent
For more information of "pairwise sequentially Markovian coalescent", see the section below.
Definition
The Pairwise Sequentially Markovian Coalescent (PSMC) is an algorithm-based method that uses genetic markers from two distinct populations to analyze demographic trends over time. It works by modeling two related haploid populations separately, as well as jointly, to infer how their respective population sizes have changed over time. PSMC also estimates the coalescence rate between lineages--the number of generations since they have shared a common ancestor--and how long it took for them to branch off from one another.
Advantages
The primary advantages of using PSMC are that it is computationally efficient, making it faster than other methods; it can be applied to all types of diploid organisms; and it provides an accurate estimation of population history despite its simplification of certain aspects such as mutation rate and recent fluctuations in population size. Additionally, this method allows researchers to accommodate different levels of uncertainty in their data without having to completely rerun the analysis.
Essential Questions and Answers on pairwise sequentially Markovian coalescent in "MISCELLANEOUS»UNFILED"
What is the Pairwise Sequentially Markovian Coalescent (PSMC)?
The Pairwise Sequentially Markovian Coalescent (PSMC) is a statistically-based reconstruction method for genetic history which uses pairwise sequence comparisons to generate inferences about population dynamics. It combines coalescent theory, which models the evolution of genetic diversity in species over time, with Markov processes that represent transitions between genetic variants over generations. In addition, PSMC provides estimates of population size changes over time, allowing researchers to explore evolutionary events in greater detail.
How does PSMC work?
The Pairwise Sequentially Markovian Coalescent (PSMC) involves using sequence comparison techniques to build up a probability representation of the coalescent process and then inferring individual markers from this simulated process. By comparing these simulated data sets across their ancestry and mutation histories, researchers can form a picture of the genetic history and population dynamics of the studied species.
How is PSMC different from other methods?
Unlike more traditional means of tracing ancestry or studying genealogy which rely upon family records or kinship analysis, PSMC uses mathematical models to infer ancestral relationships and estimate population sizes by building its models on the basis of observed sequence data rather than incomplete family trees or records. Furthermore, PSMC is capable of providing insights into historical population sizes at multiple temporal scales.
Are there any limitations to using PSMC?
One limitation with using PSMC is that it relies upon highly accurate sequence data, since the method relies heavily on the accuracy and reliability of the sequences used in order to provide meaningful results. Additionally, while the technique does provide information about temporal patterns in genetic diversity, it cannot be used as a direct measure for further selection analyses due to its focus on only a subset of individuals within each sampled populations.
What type of applications are available with PSMC?
Applications for Pairwise Sequentially Markovian Coalescent (PSMC) extend beyond its use as an ancestral reconstructor for individual populations; it can also be used as part of demographic inference studies such as those examining rates at which populations grow or decline over time or even how range expansions have shaped current distributions and diversification rates among species. Additionally, researchers can utilize PSMCo to access information regarding migration events among regions through cross-correlating probabilities determined by sequencing different populations over time.
Who developed this method?
The Pairwise Sequentially Markovian Coalescent (PSMCo) was developed independently by Drs Patterson and Reich from Harvard Medical School in 2002 in conjunction with their research into human genetics and population dynamics.
What do I need before running a PSMCo analysis?
Prior to embarking on an analysis utilizing Pairwise Sequentially Markovian Coalescent (PSMCo), you will require two datasets - one containing observation sequences from your study species from two separate moments in time; and another comprising non-parametric likelihoods obtained by sequencing various individuals within a single sample locality at both given instances in time - to construct your model.
Final Words:
Overall, the Pairwise Sequentially Markovian Coalescent (PSMC) provides a powerful tool for researchers looking to gain insight into population dynamics and evolutionary trends within various organisms. By combining efficiency with accuracy it has become increasingly popular for investigating genetic data across multiple species. Its ability to not only examine differences in allele frequency but also utilize current uncertainty levels make it incredibly useful in understanding past and present genetic structure across large taxa.