CD Genomics provides demographic inference services to help you understand the genetic diversity and historical population dynamics of various species. We offer comprehensive and tailored solutions to provide you with valuable insights into evolutionary processes, migration patterns, and the impact of environmental factors on populations.
In the last decade, the next-generation sequencing revolution has led to an exponential increase in the amount of genetic data available for many organisms. Demographic inference involves reconstructing the demographic history of a population by analyzing genetic data. Scientists can make demographic inferences from genetic data using a variety of statistical techniques, including full likelihood methods, approximate Bayesian computation (ABC) methods, locus frequency spectrum (SFS) based methods, hidden Markov models (HMM), and haplotype-based methods. All of these methods utilize aspects of genomic information. There is no straightforward method for making sound demographic inferences. The challenge is to correctly use the various methods and procedures available, select the data, choose the model to be studied, and verify that the final model fits the observed data correctly. Regardless of the method or technique used, it is important to understand that none of them can simulate the actual demographic history in all aspects and details.
Fig. 1. Flow chart of the demographic inference process. (Marchi N, et al, 2021)
CD Genomics provides comprehensive bioinformatics services for demographic inference. By leveraging expertise and cutting-edge technology, we provide tailored solutions to help our clients study population genetic histories. Our demographic inference services are used in a wide range of fields:
CD Genomics offers a one-stop demographic inference workflow with multiple phases, each of which is critical to accurate and reliable results.
(1) Data collection and pre-processing: we provide high-throughput sequencing technology to acquire large-scale genomic data, which will then be pre-processed to ensure data quality and reliability. This includes read alignment, variant calling, and quality control procedures.
(2) Model selection and implementation: our technical team selects the appropriate demographic model to best capture the population history of interest. The selected model determines the genetic parameters that will be estimated, such as population size, migration rates, and divergence times.CD Genomics provides sophisticated modeling techniques to reconstruct demographic histories. Our advanced methods extract valuable information about population size, migration rates, and evolutionary events.
(3) Simulation and validation: to validate inferred demographic models, CD Genomics performs simulations using known demographic parameters. Simulated datasets are generated to simulate different demographic scenarios and receive the same analysis pipeline as the real data.
(4) Statistical analysis and interpretation: CD Genomics provides comprehensive statistical analysis and visualization services to help researchers accurately interpret their results. These analyses involve estimating demographic parameters with relevant confidence intervals and conducting hypothesis tests to evaluate different evolutionary scenarios.
Based on advanced modeling and bioinformatics techniques, CD Genomics offers tailored solutions for demographic inference to reveal the genetic history and population dynamics of various species. By leveraging demographic inference, we can help you elucidate the evolutionary processes behind genetic variation, thereby facilitating advances in fields such as human evolutionary genetics, conservation biology, and crop improvement. If you are interested in our services, please contact us for more detailed information.