An FPT haplotyping algorithm on pedigrees with a small number of sites

<p>Abstract</p> <p>Background</p> <p>Genetic disease studies investigate relationships between changes in chromosomes and genetic diseases. Single haplotypes provide useful information for these studies but extracting single haplotypes directly by biochemical methods is expensive. A computational method to infer haplotypes from genotype data is therefore important. We investigate the problem of computing the minimum number of recombination events for general pedigrees with a small number of sites for all members.</p> <p>Results</p> <p>We show that this NP-hard problem can be parametrically reduced to the Bipartization by Edge Removal problem with additional parity constraints. We solve this problem with an exact algorithm that runs in <inline-formula><graphic file="1748-7188-6-8-i1.gif"/></inline-formula> time, where <it>n </it>is the number of members, <it>m </it>is the number of sites, and <it>k </it>is the number of recombination events.</p> <p>Conclusions</p> <p>This algorithm infers haplotypes for a small number of sites, which can be useful for genetic disease studies to track down how changes in haplotypes such as recombinations relate to genetic disease.</p

Haplotype inference in general pedigrees with two sites

<p>Abstract</p> <p>Background</p> <p>Genetic disease studies investigate relationships between changes in chromosomes and genetic diseases. Single haplotypes provide useful information for these studies but extracting single haplotypes directly by biochemical methods is expensive. A computational method to infer haplotypes from genotype data is therefore important. We investigate the problem of computing the minimum number of recombination events for general pedigrees with two sites for all members.</p> <p>Results</p> <p>We show that this NP-hard problem can be parametrically reduced to the Bipartization by Edge Removal problem and therefore can be solved by an <it>O</it>(2<it>^k</it> · <it>n</it>²) exact algorithm, where <it>n</it> is the number of members and <it>k</it> is the number of recombination events.</p> <p>Conclusions</p> <p>Our work can therefore be useful for genetic disease studies to track down how changes in haplotypes such as recombinations relate to genetic disease.</p

Gut microbiota and diabetes: from pathogenesis to therapeutic perspective

More than several hundreds of millions of people will be diabetic and obese over the next decades in front of which the actual therapeutic approaches aim at treating the consequences rather than causes of the impaired metabolism. This strategy is not efficient and new paradigms should be found. The wide analysis of the genome cannot predict or explain more than 10–20% of the disease, whereas changes in feeding and social behavior have certainly a major impact. However, the molecular mechanisms linking environmental factors and genetic susceptibility were so far not envisioned until the recent discovery of a hidden source of genomic diversity, i.e., the metagenome. More than 3 million genes from several hundreds of species constitute our intestinal microbiome. First key experiments have demonstrated that this biome can by itself transfer metabolic disease. The mechanisms are unknown but could be involved in the modulation of energy harvesting capacity by the host as well as the low-grade inflammation and the corresponding immune response on adipose tissue plasticity, hepatic steatosis, insulin resistance and even the secondary cardiovascular events. Secreted bacterial factors reach the circulating blood, and even full bacteria from intestinal microbiota can reach tissues where inflammation is triggered. The last 5 years have demonstrated that intestinal microbiota, at its molecular level, is a causal factor early in the development of the diseases. Nonetheless, much more need to be uncovered in order to identify first, new predictive biomarkers so that preventive strategies based on pre- and probiotics, and second, new therapeutic strategies against the cause rather than the consequence of hyperglycemia and body weight gain

A Deep Neural Network for Simultaneous Estimation of b Jet Energy and Resolution

We describe a method to obtain point and dispersion estimates for the energies of jets arising from b quarks produced in proton-proton collisions at an energy of s = 13 TeV at the CERN LHC. The algorithm is trained on a large sample of simulated b jets and validated on data recorded by the CMS detector in 2017 corresponding to an integrated luminosity of 41 fb - 1 . A multivariate regression algorithm based on a deep feed-forward neural network employs jet composition and shape information, and the properties of reconstructed secondary vertices associated with the jet. The results of the algorithm are used to improve the sensitivity of analyses that make use of b jets in the final state, such as the observation of Higgs boson decay to b b ¯

Measurement of B_{s}^{0} meson production in pp and PbPb collisions at \sqrt{SNN}

The production cross sections of B_{s}^{0} mesons and charge conjugates are measured in proton-proton (pp) and PbPb collisions via the exclusive decay channel B_{s}^{0}→J/ψϕ→μ^{+}μ^{−}K^{+}K^{−} at a center-of-mass energy of 5.02 TeV per nucleon pair and within the rapidity range |y|<2.4 using the CMS detector at the LHC. The pp measurement is performed as a function of transverse momentum (p_{T}) of the B_{s}^{0} mesons in the range of 7 to 50 GeV/c and is compared to the predictions of perturbative QCD calculations. The B_{s}^{0} production yield in PbPb collisions is measured in two p_{T} intervals, 7 to 15 and 15 to 50 GeV/c, and compared to the yield in pp collisions in the same kinematic region. The nuclear modification factor (R_{AA}) is found to be 1.5±0.6(stat)±0.5(syst) for 7–15 GeV/c, and 0.87±0.30(stat)±0.17(syst) for 15–50 GeV/c, respectively. Within current uncertainties, the B_{s}^{0} results are consistent with models of strangeness enhancement, and suppression by parton energy loss, as observed for the B+ mesons

Measurement of the tt¯ production cross section, the top quark mass, and the strong coupling constant using dilepton events in pp collisions at √s = 13 TeV

A measurement of the top quark–antiquark pair production cross section σtt¯ in proton–proton collisions at a centre-of-mass energy of 13TeV is presented. The data correspond to an integrated luminosity of 35.9fb−1, recorded by the CMS experiment at the CERN LHC in 2016. Dilepton events (e ± μ ∓, μ+μ−, e+e−) are selected and the cross section is measured from a likelihood fit. For a top quark mass parameter in the simulation of mMCt=172.5GeV the fit yields a measured cross section σtt¯=803±2(stat)±25(syst)±20(lumi)pb, in agreement with the expectation from the standard model calculation at next-to-next-to-leading order. A simultaneous fit of the cross section and the top quark mass parameter in the POWHEG simulation is performed. The measured value of mMCt=172.33±0.14(stat)+0.66−0.72(syst)GeV is in good agreement with previous measurements. The resulting cross section is used, together with the theoretical prediction, to determine the top quark mass and to extract a value of the strong coupling constant with different sets of parton distribution functions

Search for contact interactions and large extra dimensions in the dilepton mass spectra from proton-proton collisions at \sqrt{s} = 13 TeV

A search for nonresonant excesses in the invariant mass spectra of electron and muon pairs is presented. The analysis is based on data from proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the CMS experiment in 2016, corresponding to a total integrated luminosity of 36 fb^{-1}. No significant deviation from the standard model is observed. Limits are set at 95% confidence level on energy scales for two general classes of nonresonant models. For a class of fermion contact interaction models, lower limits ranging from 20 to 32 TeV are set on the characteristic compositeness scale Λ. For the Arkani-Hamed, Dimopoulos, and Dvali model of large extra dimensions, the first results in the dilepton final state at 13 TeV are reported, and values of the ultraviolet cutoff parameter Λ_{T} below 6.9 TeV are excluded. A combination with recent CMS diphoton results improves this exclusion to Λ_{T} below 7.7 TeV, providing the most sensitive limits to date in nonhadronic final states

Measurement of the energy density as a function of pseudorapidity in proton-proton collisions at root \sqrt{s} = 13 TeV

A measurement of the energy density in proton–proton collisions at a centre-of-mass energy of s√=13 TeV is presented. The data have been recorded with the CMS experiment at the LHC during low luminosity operations in 2015. The energy density is studied as a function of pseudorapidity in the ranges −6.6<η<−5.2 and 3.15<|η|<5.20. The results are compared with the predictions of several models. All the models considered suggest a different shape of the pseudorapidity dependence compared to that observed in the data. A comparison with LHC proton–proton collision data at s√=0.9 and 7TeV confirms the compatibility of the data with the hypothesis of limiting fragmentation

Constraints on anomalous HVV couplings from the production of Higgs bosons decaying to τ lepton pairs

A study is presented of anomalous HVV interactions of the Higgs boson, including its CP properties. The study uses Higgs boson candidates produced mainly in vector boson fusion and gluon fusion that subsequently decay to a pair of τ leptons. The data were recorded by the CMS experiment at the LHC in 2016 at a center-of-mass energy of 13 TeV and correspond to an integrated luminosity of 35.9  fb−1. A matrix element technique is employed for the analysis of anomalous interactions. The results are combined with those from the H→4ℓ decay channel presented earlier, yielding the most stringent constraints on anomalous Higgs boson couplings to electroweak vector bosons expressed as effective cross section fractions and phases: the CP-violating parameter fa3cos(ϕa3)=(0.00±0.27)×10−3 and the CP-conserving parameters fa2cos(ϕa2)=(0.08+1.04−0.21)×10−3, fΛ1cos(ϕΛ1)=(0.00+0.53−0.09)×10−3, and fZγΛ1cos(ϕZγΛ1)=(0.0+1.1−1.3)×10−3. The current dataset does not allow for precise constraints on CP properties in the gluon fusion process. The results are consistent with standard model expectations