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SummaryExtremely large datasets are impossible or very difficult for humans to comprehend by standard mental approaches. Intuitive visualization of genetic variants in genomic sequencing data could help in the review and confirmation process of variants called by automated variant calling programs. To help facilitate interpretation of genetic variant next-generation sequencing (NGS) data we developed VisVariant, a customizable visualization tool that creates a figure showing the overlapping sequence information of thousands of individual reads including the variant and flanking regions.Availability and implementationDetailed information on how to download, install and run VisVariant together with an example is available on our github website [https://github.com/hugging-biorxiv/visvariant].

Background / Objectives Background: Persistent infection with high-risk human papillomavirus (hr-HPV) is an important co-factor in cervical cancer development and is associated with DNA methylation on both human and viral genes. The S5 DNA methylation classifier, based on target CpG sites of the human gene EPB41L3, and viral late gene regions of HPV16, HPV18, HPV31 and HPV33 (Lorincz A et al., 2016) has demonstrated better performance for detection of CIN2/3 women than either HPV16/18 genotyping, cytology or combination. We tested the performance of S5 in detecting invasive cancers versus pre-cancers and quantified the degree of separation between normal/CIN1, CIN2/3 and invasive cancer S5 scores. Results Methods: Methylation status of the S5 selected CpG sites was tested in DNA extracted from formalin-fixed biopsies from the Scottish HPV Archive (UK, n=24) and PreservCyt collected exfoliated cervical cell samples from the Scottish HPV Archive (UK, n=48) and the International Agency for Research on Cancer (Spain, n=100).Samples were histologically defined as negative/CIN1 (n=33), CIN2/3 (n=65) and invasive cancer (n=74). DNA bisulfite conversion was carried out and followed by pyrosequencing for the 6 components of S5. Average methylation was calculated for each marker to define the S5 score. Conclusion Results: Methylation at all sites increased proportionally with disease severity with a Cuzick trend value of z = 9.2933 (p < 2.2x10-16). The separation of normal/CIN1 from CIN2/3 and from cancer was highly significant (Mann Whitney test, both p < 0.0001). S5 also showed highly significant difference between CIN2/3 and invasive 327/490 cancer from both IARC-Spain (p < 0.0001) and Scottish (p < 0.003) cohorts. Receiver operating characteristic (ROC) curves were used to assess the diagnostic potential of S5 in differentiating cancers from CIN2/3. The area under the ROC curve (AUC) was 0.86 (CI 95%: 0.7965 to 0.9131, p < 0.0001) with a sensitivity of 79.8% and a specificity of 83.1%, based on a cut-off at highest Youden J index. References Conclusion: The S5 methylation classifier may be useful in cervical screening programs for differentiating pre-cancers from invasive cervical cancers in women infected with hr-HPV. Although the separation was very good, there is room for improvement in S5 by addition of new markers

International audience; Air quality models that generate the concentrations of semi-volatile and other condensable organic compounds using an explicit reaction mechanism require estimates of the physical and thermodynamic properties of the compounds that affect gas/aerosol partitioning: vapour pressure (as a subcooled liquid), and activity coefficients in the aerosol phase. The model of Griffin, Kleeman and co-workers (e.g., Griffin et al., 2003; Kleeman et al., 1999) assumes that aerosol particles consist of an aqueous phase, containing inorganic electrolytes and soluble organic compounds, and a hydrophobic phase containing mainly primary hydrocarbon material. Thirty eight semi-volatile reaction products are grouped into ten surrogate species which partition between the gas phase and both phases in the aerosol. Activity coefficients of the organic compounds are calculated using UNIFAC. In a companion paper (Clegg et al., 2008) we examine the likely uncertainties in the vapour pressures of the semi-volatile compounds and their effects on partitioning over a range of atmospheric relative humidities. In this work a simulation for the South Coast Air Basin surrounding Los Angeles, using lower vapour pressures of the semi-volatile surrogate compounds consistent with estimated uncertainties in the boiling points on which they are based, yields a doubling of the predicted 24-h average secondary organic aerosol concentrations. The dependency of organic compound partitioning on the treatment of inorganic electrolytes in the air quality model, and the performance of this component of the model, are determined by analysing the results of a trajectory calculation using an extended version of the Aerosol Inorganics Model of Wexler and Clegg (2002). Simplifications are identified where substantial efficiency gains can be made, principally: the omission of dissociation of the organic acid surrogates; restriction of aerosol organic compounds to one of the two phases (aqueous or hydrophobic) where equilibrium calculations suggest partitioning strongly in either direction; a single calculation of activity coefficients of the organic compounds for simulations where they are determined by the presence of one component at high concentration in either phase (i.e., water in the aqueous phase, or a hydrocarbon surrogate compound P8 in the hydrophobic phase) and are therefore almost invariant. The implications of the results for the development of aerosol models are discussed.

International audience; Air quality models that generate the concentrations of semi-volatile and other condensable organic compounds using an explicit reaction mechanism require estimates of the vapour pressures of the organic compounds that partition between the aerosol and gas phases. The model of Griffin, Kleeman and co-workers (e.g., Griffin et al., 2005) assumes that aerosol particles consist of an aqueous phase, containing inorganic electrolytes and soluble organic compounds, and a hydrophobic phase containing mainly primary hydrocarbon material. Thirty eight semi-volatile reaction products are grouped into ten surrogate species. In Part 1 of this work (Clegg et al., 2008) the thermodynamic elements of the gas/aerosol partitioning calculation are examined, and the effects of uncertainties and approximations assessed, using a simulation for the South Coast Air Basin around Los Angeles as an example. Here we compare several different methods of predicting vapour pressures of organic compounds, and use the results to determine the likely uncertainties in the vapour pressures of the semi-volatile surrogate species in the model. These are typically an order of magnitude or greater, and are further increased when the fact that each compound represents a range of reaction products (for which vapour pressures can be independently estimated) is taken into account. The effects of the vapour pressure uncertainties associated with the water-soluble semi-volatile species are determined over a wide range of atmospheric liquid water contents. The vapour pressures of the eight primary hydrocarbon surrogate species present in the model, which are normally assumed to be involatile, are also predicted. The results suggest that they have vapour pressures high enough to exist in both the aerosol and gas phases under typical atmospheric conditions.

International audience; Air quality models that generate the concentrations of semi-volatile and other condensable organic compounds using an explicit reaction mechanism require estimates of the physical and thermodynamic properties of the compounds that affect gas/aerosol partitioning: vapour pressure (as a subcooled liquid), and activity coefficients in the aerosol phase. The model of Griffin, Kleeman and co-workers (e.g., Griffin et al., 1999; Kleeman et al., 1999) assumes that aerosol particles consist of an aqueous phase, containing inorganic electrolytes and soluble organic compounds, and a hydrophobic phase containing mainly primary hydrocarbon material. Thirty eight semi-volatile reaction products are grouped into ten surrogate species which partition between the gas phase and both phases in the aerosol. Activity coefficients of the organic compounds are calculated using UNIFAC. In a companion paper (Clegg et al., 2007) we examine the likely uncertainties in the vapour pressures of the semi-volatile compounds and their effects on partitioning over a range of atmospheric relative humidities. In this work a simulation for the South Coast Air Basin surrounding Los Angeles, using lower vapour pressures of the semi-volatile surrogate compounds consistent with estimated uncertainties in the boiling points on which they are based, yields a doubling of the predicted 24-h average secondary organic aerosol concentrations. The dependency of organic compound partitioning on the treatment of inorganic electrolytes in the air quality model, and the performance of this component of the model, are determined by analysing the results of a trajectory calculation using an extended version of the Aerosol Inorganics Model of Wexler and Clegg (2002). Simplifications are identified where substantial efficiency gains can be made, principally: the omission of dissociation of the organic acid surrogates; restriction of aerosol organic compounds to one of the two phases (aqueous or hydrophobic) where equilibrium calculations suggest partitioning strongly in either direction; a single calculation of activity coefficients of the organic compounds for simulations where they are determined by the presence of one component at high concentration in either phase (i.e., water in the aqueous phase, or a hydrocarbon surrogate compound P8 in the hydrophobic phase) and are therefore almost invariant. The implications of the results for the development of aerosol models are discussed.

The multiobjective quadratic assignment problem is an NP-complete problem with a multitude of real-world applications. The specific application addressed is the minimization of communication flows in a heterogenous mix of unmanned aerial vehicles. Developed is a multiobjective approach to solving the general mQAP for this UAV application. The combinatoric nature of this problem calls for a stochastic search algorithm; moreover, the multiobjective fast messy genetic algorithm (MOMGA-II) [Jesse Zydallis (2003)] is used for experimentation. Results indicate that much of the Pareto optimal points are found.