Dataset Information

New statistical methods for estimation of recombination fractions in F₂ population.

ABSTRACT:

Background

Dominant markers in an F₂ population or a hybrid population have much less linkage information in repulsion phase than in coupling phase. Linkage analysis produces two separate complementary marker linkage maps that have little use in disease association analysis and breeding. There is a need to develop efficient statistical methods and computational algorithms to construct or merge a complete linkage dominant marker maps. The key for doing so is to efficiently estimate recombination fractions between dominant markers in repulsion phases.

Result

We proposed an expectation least square (ELS) algorithm and binomial analysis of three-point gametes (BAT) for estimating gamete frequencies from F₂ dominant and codominant marker data, respectively. The results obtained from simulated and real genotype datasets showed that the ELS algorithm was able to accurately estimate frequencies of gametes and outperformed the EM algorithm in estimating recombination fractions between dominant loci and recovering true linkage maps of 6 dominant loci in coupling and unknown linkage phases. Our BAT method also had smaller variances in estimation of two-point recombination fractions than the EM algorithm.

Conclusion

ELS is a powerful method for accurate estimation of gamete frequencies in dominant three-locus system in an F₂ population and BAT is a computationally efficient and fast method for estimating frequencies of three-point codominant gametes.

SUBMITTER: Tan YD

PROVIDER: S-EPMC5629630 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Publications

New statistical methods for estimation of recombination fractions in F<sub>2</sub> population.

Tan Yuan-De YD Zhang Xiang H F XHF Mo Qianxing Q

BMC bioinformatics 20171003 Suppl 11

<h4>Background</h4>Dominant markers in an F<sub>2</sub> population or a hybrid population have much less linkage information in repulsion phase than in coupling phase. Linkage analysis produces two separate complementary marker linkage maps that have little use in disease association analysis and breeding. There is a need to develop efficient statistical methods and computational algorithms to construct or merge a complete linkage dominant marker maps. The key for doing so is to efficiently esti ...[more]

PMID: 28984187

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Project description:Genetic recombination is a very important evolutionary mechanism that mixes parental haplotypes and produces new raw material for organismal evolution. As a result, information on recombination rates is critical for biological research. In this paper, we introduce a new extremely fast open-source software package (FastEPRR) that uses machine learning to estimate recombination rate [Formula: see text] (=[Formula: see text]) from intraspecific DNA polymorphism data. When [Formula: see text] and the number of sampled diploid individuals is large enough ([Formula: see text]), the variance of [Formula: see text] remains slightly smaller than that of [Formula: see text] The new estimate [Formula: see text] (calculated by averaging [Formula: see text] and [Formula: see text]) has the smallest variance of all cases. When estimating [Formula: see text], the finite-site model was employed to analyze cases with a high rate of recurrent mutations, and an additional method is proposed to consider the effect of variable recombination rates within windows. Simulations encompassing a wide range of parameters demonstrate that different evolutionary factors, such as demography and selection, may not increase the false positive rate of recombination hotspots. Overall, accuracy of FastEPRR is similar to the well-known method, LDhat, but requires far less computation time. Genetic maps for each human population (YRI, CEU, and CHB) extracted from the 1000 Genomes OMNI data set were obtained in less than 3 d using just a single CPU core. The Pearson Pairwise correlation coefficient between the [Formula: see text] and [Formula: see text] maps is very high, ranging between 0.929 and 0.987 at a 5-Mb scale. Considering that sample sizes for these kinds of data are increasing dramatically with advances in next-generation sequencing technologies, FastEPRR (freely available at http://www.picb.ac.cn/evolgen/) is expected to become a widely used tool for establishing genetic maps and studying recombination hotspots in the population genomic era.

Project description:BACKGROUND:Almost all countries without complete vital registration systems have data on deaths collected by hospitals. However, these data have not been widely used to estimate cause of death (COD) patterns in populations because only a non-representative fraction of people in these countries die in health facilities. Methods that can exploit hospital mortality statistics to reliably estimate community COD patterns are required to strengthen the evidence base for disease and injury control programs. We propose a method that weights hospital-certified causes by the probability of death to estimate population cause-specific mortality fractions (CSMFs). METHODS:We used an established verbal autopsy instrument (VAI) to collect data from hospital catchment areas in Chandpur and Comilla Districts, Bangladesh, and Bohol province, the Philippines, between 2011 and 2014, along with demographic covariates for each death. Hospital medical certificates of cause of death (death certificates) were collected and mapped to the corresponding cause categories of the VAI. Tariff 2.0 was used to assign a COD for community deaths. Logistic regression models were created for broad causes in each country to calculate the probability of in-hospital death, given a set of covariate values. The reweighted CSMFs for deaths in the hospital catchment population, represented by each hospital death, were calculated from the corresponding regression models. RESULTS:We collected data on 4228 adult deaths in the Philippines and 3725 deaths in Bangladesh. Short time to hospital and education were consistently associated with in-hospital death in the Philippines and absence of a disability was consistently associated with in-hospital death in Bangladesh. Non-communicable diseases (excluding stroke) and stroke were the leading causes of death in both the Philippines (33.9%, 19.1%) and Bangladesh (46.1%, 21.1%) according to the reweighted method. The reweighted method generally estimated CSMFs that fell between those derived from hospitals and those diagnosed by Tariff 2.0. CONCLUSIONS:Statistical methods can be used to derive estimates of cause-specific probability of death in-hospital for Bangladesh and the Philippines to generate population CSMFs. In regions where hospital death certification is of reasonable quality and routine verbal autopsy is not applied, these estimates could be applied to generate cost-effective and robust CSMFs for the population.

Dataset Information

New statistical methods for estimation of recombination fractions in F₂ population.

Background

Result

Conclusion

Publications

New statistical methods for estimation of recombination fractions in F<sub>2</sub> population.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

New statistical methods for estimation of recombination fractions in F2 population.

Background

Result

Conclusion

Publications

New statistical methods for estimation of recombination fractions in F<sub>2</sub> population.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

New statistical methods for estimation of recombination fractions in F₂ population.