MutationDistiller – User-driven identification of disease mutations

In rare genetic diseases, a single genetic alteration can be enough to cause a severe disorder. Recent advances in genetic research have introduced exome or genome sequencing into clinical care. However, each sequencing run delivers a myriad of candidate variants that have to be sifted through in the hunt for the causative mutation - a major data challenge, for which researchers and clinicians have to rely on computer tools. With MutationDistiller, we have developed a freely available online tool to analyse whole exome sequencing data in a user-driven fashion. The tool aims at clinicians and researchers without bioinformatic experience who are working with real patient data, and allows them to distil the most likely causative variants from the sea of candidates. By uploading the patient’s genetic information and adding information on the symptoms, they can combine genotype and phenotype to find the culprit. MutationDistiller allows a wide range of phenotype data, such as HPO, OMIM and Orphanet entries, gene panels, expression data, Gene Ontology terms, and affected pathways. In the output, the program provides an ordered list of candidate alterations matching the user-defined criteria. In addition, crucial data on the alteration and the affected gene can be reviewed at a glance. This thesis describes the program, its background and usage, and compares it to current state-of-the-art tools. When assessing the tool, we found that it matches or out-competes similar software and is able to find the causative variant in a majority of cases. Moreover, its user-friendliness makes it a handy tool for clinicians and researchers, as is reflected by its usage: MutationDistiller routinely sees over 1,000 cases per month and has been used in over 14,000 cases at the time of writing. Thus, MutationDistiller has already found its way into the clinic. The tool, comprehensive documentation and example cases are freely available at https://www.mutationdistiller.org

MutationDistiller: user-driven identification of pathogenic DNA variants

MutationDistiller is a freely available online tool for user-driven analyses of Whole Exome Sequencing data. It offers a user-friendly interface aimed at clinicians and researchers, who are not necessarily bioinformaticians. MutationDistiller combines Mutation- Taster’s pathogenicity predictions with a phenotypebased approach. Phenotypic information is not limited to symptoms included in the Human Phenotype Ontology (HPO), but may also comprise clinical diagnoses and the suspected mode of inheritance. The search can be restricted to lists of candidate genes (e.g. virtual gene panels) and by tissue-specific gene expression. The inclusion of GeneOntology (GO) and metabolic pathways facilitates the discovery of hitherto unknown disease genes. In a novel approach, we trained MutationDistiller’s HPO-based prioritization on authentic genotype–phenotype sets obtained from ClinVar and found it to match or outcompete current prioritization tools in terms of accuracy. In the output, the program provides a list of potential disease mutations ordered by the likelihood of the affected genes to cause the phenotype. MutationDistiller provides links to gene-related information from various resources. It has been extensively tested by clinicians and their suggestions have been valued in many iterative cycles of revisions. The tool, a comprehensive documentation and examples are freely available at https://www.mutationdistiller.org

RegulationSpotter: annotation and interpretation of extratranscriptic DNA variants

RegulationSpotter is a web-based tool for the user-friendly annotation and interpretation of DNA variants located outside of protein-coding transcripts (extratranscriptic variants). It is designed for clinicians and researchers who wish to assess the potential impact of the considerable number of non-coding variants found in Whole Genome Sequencing runs. It annotates individual variants with underlying regulatory features in an intuitive way by assessing over 100 genome-wide annotations. Additionally, it calculates a score, which reflects the regulatory potential of the variant region. Its dichotomous classifications, ‘functional’ or ‘non-functional’, and a human-readable presentation of the underlying evidence allow a biologically meaningful interpretation of the score. The output shows key aspects of every variant and allows rapid access to more detailed information about its possible role in gene regulation. RegulationSpotter can either analyse single variants or complete VCF files. Variants located within protein-coding transcripts are automatically assessed by MutationTaster as well as by RegulationSpotter to account for possible intragenic regulatory effects. RegulationSpotter offers the possibility of using phenotypic data to focus on known disease genes or genomic elements interacting with them. RegulationSpotter is freely available at https://www.regulationspotter.org

A systematic, large-scale comparison of transcription factor binding site models

Background The modelling of gene regulation is a major challenge in biomedical research. This process is dominated by transcription factors (TFs) and mutations in their binding sites (TFBSs) may cause the misregulation of genes, eventually leading to disease. The consequences of DNA variants on TF binding are modelled in silico using binding matrices, but it remains unclear whether these are capable of accurately representing in vivo binding. In this study, we present a systematic comparison of binding models for 82 human TFs from three freely available sources: JASPAR matrices, HT-SELEX-generated models and matrices derived from protein binding microarrays (PBMs). We determined their ability to detect experimentally verified “real” in vivo TFBSs derived from ENCODE ChIP-seq data. As negative controls we chose random downstream exonic sequences, which are unlikely to harbour TFBS. All models were assessed by receiver operating characteristics (ROC) analysis. Results While the area- under-curve was low for most of the tested models with only 47 % reaching a score of 0.7 or higher, we noticed strong differences between the various position-specific scoring matrices with JASPAR and HT-SELEX models showing higher success rates than PBM-derived models. In addition, we found that while TFBS sequences showed a higher degree of conservation than randomly chosen sequences, there was a high variability between individual TFBSs. Conclusions Our results show that only few of the matrix-based models used to predict potential TFBS are able to reliably detect experimentally confirmed TFBS. We compiled our findings in a freely accessible web application called ePOSSUM (http:/mutationtaster.charite.de/ePOSSUM/) which uses a Bayes classifier to assess the impact of genetic alterations on TF binding in user-defined sequences. Additionally, ePOSSUM provides information on the reliability of the prediction using our test set of experimentally confirmed binding sites

A study of CP violation in B-+/- -> DK +/- and B-+/- -> D pi(+/-) decays with D -> (KSK +/-)-K-0 pi(-/+) final states

A first study of CP violation in the decay modes $B^\pm\to [K^0_{\rm S} K^\pm \pi^\mp]_D h^\pm$ and $B^\pm\to [K^0_{\rm S} K^\mp \pi^\pm]_D h^\pm$, where $h$ labels a $K$ or $\pi$ meson and $D$ labels a $D^0$ or $\overline{D}^0$ meson, is performed. The analysis uses the LHCb data set collected in $pp$ collisions, corresponding to an integrated luminosity of 3 fb$^{-1}$. The analysis is sensitive to the CP-violating CKM phase $\gamma$ through seven observables: one charge asymmetry in each of the four modes and three ratios of the charge-integrated yields. The results are consistent with measurements of $\gamma$ using other decay modes

Study of forward Z + jet production in pp collisions at √s=7 TeV

A measurement of the $Z(\rightarrow\mu^+\mu^-)$+jet production cross-section in $pp$ collisions at a centre-of-mass energy $\sqrt{s} = 7$ TeV is presented. The analysis is based on an integrated luminosity of $1.0\,\text{fb}^{-1}$ recorded by the LHCb experiment. Results are shown with two jet transverse momentum thresholds, 10 and 20 GeV, for both the overall cross-section within the fiducial volume, and for six differential cross-section measurements. The fiducial volume requires that both the jet and the muons from the Z boson decay are produced in the forward direction ($2.0<\eta<4.5$). The results show good agreement with theoretical predictions at the second-order expansion in the coupling of the strong interaction.A measurement of the $Z(\rightarrow\mu^+\mu^-)$+jet production cross-section in $pp$ collisions at a centre-of-mass energy $\sqrt{s} = 7$ TeV is presented. The analysis is based on an integrated luminosity of $1.0\,\text{fb}^{-1}$ recorded by the LHCb experiment. Results are shown with two jet transverse momentum thresholds, 10 and 20 GeV, for both the overall cross-section within the fiducial volume, and for six differential cross-section measurements. The fiducial volume requires that both the jet and the muons from the Z boson decay are produced in the forward direction ($2.0<\eta<4.5$). The results show good agreement with theoretical predictions at the second-order expansion in the coupling of the strong interaction

Search for the lepton flavour violating decay tau(-) -&gt; mu(-)mu(+)mu(-)

A search for the lepton flavour violating decay $\tau^-\rightarrow\mu^-\mu^+\mu^-$ is performed with the LHCb experiment. The data sample corresponds to an integrated luminosity of 1.0 fb$^{−1}$ of proton-proton collisions at a centre-of-mass energy of 7 TeV and 2.0 fb$^{−1}$ at 8 TeV. No evidence is found for a signal, and a limit is set at 90% confidence level on the branching fraction, $\mathcal{B}(\tau^-\rightarrow\mu^-\mu^+\mu^-)<4.6\times10^{−8}$.A search for the lepton flavour violating decay τ$^{−}$ → μ$^{−}$ μ$^{+}$ μ$^{−}$ is performed with the LHCb experiment. The data sample corresponds to an integrated luminosity of 1.0 fb$^{−1}$ of proton-proton collisions at a centre-of-mass energy of 7 TeV and 2.0 fb$^{−1}$ at 8 TeV. No evidence is found for a signal, and a limit is set at 90% confidence level on the branching fraction, $\mathrm{\mathcal{B}}\left({\tau}^{-}\to {\mu}^{-}{\mu}^{+}{\mu}^{-}\right)<4.6\times {10}^{-8}$ .A search for the lepton flavour violating decay $\tau^-\to \mu^-\mu^+\mu^-$ is performed with the LHCb experiment. The data sample corresponds to an integrated luminosity of $1.0\mathrm{\,fb}^{-1}$ of proton-proton collisions at a centre-of-mass energy of $7\mathrm{\,Te\kern -0.1em V}$ and $2.0\mathrm{\,fb}^{-1}$ at $8\mathrm{\,Te\kern -0.1em V}$. No evidence is found for a signal, and a limit is set at $90\%$ confidence level on the branching fraction, $\mathcal{B}(\tau^-\to \mu^-\mu^+\mu^-) < 4.6 \times 10^{-8}$

Measurement of Upsilon production in collisions at root s=2.76 TeV

The production of $\Upsilon(1S)$, $\Upsilon(2S)$ and $\Upsilon(3S)$ mesons decaying into the dimuon final state is studied with the LHCb detector using a data sample corresponding to an integrated luminosity of 3.3 $pb^{-1}$ collected in proton-proton collisions at a centre-of-mass energy of $\sqrt{s}=2.76$ TeV. The differential production cross-sections times dimuon branching fractions are measured as functions of the $\Upsilon$ transverse momentum and rapidity, over the ranges $p_{\rm T} Upsilon(1S) X) x B(Upsilon(1S) -> mu+mu-) = 1.111 +/- 0.043 +/- 0.044 nb, sigma(pp -> Upsilon(2S) X) x B(Upsilon(2S) -> mu+mu-) = 0.264 +/- 0.023 +/- 0.011 nb, sigma(pp -> Upsilon(3S) X) x B(Upsilon(3S) -> mu+mu-) = 0.159 +/- 0.020 +/- 0.007 nb, where the first uncertainty is statistical and the second systematic