| 1. |
- Thomas, HS, et al.
(författare)
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- 2019
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swepub:Mat__t
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| 2. |
- Menden, MP, et al.
(författare)
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
- 2019
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
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Tidskriftsartikel (refereegranskat)abstract
- The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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| 3. |
- Zhang, Y., et al.
(författare)
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Dark Energy Surveyed Year 1 results : calibration of cluster mis-centring in the redMaPPer catalogues
- 2019
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Ingår i: Monthly notices of the Royal Astronomical Society. - : OXFORD UNIV PRESS. - 0035-8711 .- 1365-2966. ; 487:2, s. 2578-2593
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Tidskriftsartikel (refereegranskat)abstract
- The centre determination of a galaxy cluster from an optical cluster finding algorithm can be offset from theoretical prescriptions or N-body definitions of its host halo centre. These offsets impact the recovered cluster statistics, affecting both richness measurements and the weak lensing shear profile around the clusters. This paper models the centring performance of the redMaPPer cluster finding algorithm using archival X-ray observations of redMaPPer-selected clusters. Assuming the X-ray emission peaks as the fiducial halo centres, and through analysing their offsets to the redMaPPer centres, we find that similar to 75 +/- 8 per cent of the redMaPPer clusters are well centred and the mis-centred offset follows a Gamma distribution in normalized, projected distance. These mis-centring offsets cause a systematic underestimation of cluster richness relative to the well-centred clusters, for which we propose a descriptive model. Our results enable the DES Y1 cluster cosmology analysis by characterizing the necessary corrections to both the weak lensing and richness abundance functions of the DES Y1 redMaPPer cluster catalogue.
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| 4. |
- Zhang, Y., et al.
(författare)
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Galaxies in X-ray selected clusters and groups in Dark Energy Survey data - II. Hierarchical Bayesian modelling of the red-sequence galaxy luminosity function
- 2019
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Ingår i: Monthly notices of the Royal Astronomical Society. - : OXFORD UNIV PRESS. - 0035-8711 .- 1365-2966. ; 488:1, s. 1-17
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Tidskriftsartikel (refereegranskat)abstract
- Using similar to 100 X-ray selected clusters in the Dark Energy Survey Science Verification data, we constrain the luminosity function ( LF) of cluster red-sequence galaxies as a function of redshift. This is the first homogeneous optical/X-ray sample large enough to constrain the evolution of the LF simultaneously in redshift ( 0.1 < z < 1.05) and cluster mass ( 13.5 <= log(10)( M-200crit) similar to< 15.0). We pay particular attention to completeness issues and the detection limit of the galaxy sample. We then apply a hierarchical Bayesian model to fit the cluster galaxy LFs via a Schechter function, including its characteristic break ( m*) to a faint end power-law slope ( alpha). Our method enables us to avoid known issues in similar analyses based on stacking or binning the clusters. We find weak and statistically insignificant (similar to 1.9 sigma) evolution in the faint end slope alpha versus redshift. We also find no dependence in alpha or m* with the X-ray inferred cluster masses. However, the amplitude of the LF as a function of cluster mass is constrained to similar to 20 per cent precision. As a by-product of our algorithm, we utilize the correlation between the LF and cluster mass to provide an improved estimate of the individual cluster masses as well as the scatter in true mass given the X-ray inferred masses. This technique can be applied to a larger sample of X-ray or optically selected clusters from the Dark Energy Survey, significantly improving the sensitivity of the analysis.
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| 5. |
- Malz, A., et al.
(författare)
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The Photometric LSST Astronomical Time-series Classification Challenge PLAsTiCC : Selection of a Performance Metric for Classification Probabilities Balancing Diverse Science Goals
- 2019
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Ingår i: Astronomical Journal. - : American Astronomical Society. - 0004-6256 .- 1538-3881. ; 158:5
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Tidskriftsartikel (refereegranskat)abstract
- Classification of transient and variable light curves is an essential step in using astronomical observations to develop an understanding of the underlying physical processes from which they arise. However, upcoming deep photometric surveys, including the Large Synoptic Survey Telescope (LSST), will produce a deluge of low signal-to-noise data for which traditional type estimation procedures are inappropriate. Probabilistic classification is more appropriate for such data but is incompatible with the traditional metrics used on deterministic classifications. Furthermore, large survey collaborations like LSST intend to use the resulting classification probabilities for diverse science objectives, indicating a need for a metric that balances a variety of goals. We describe the process used to develop an optimal performance metric for an open classification challenge that seeks to identify probabilistic classifiers that can serve many scientific interests. The Photometric LSST Astronomical Time-series Classification Challenge (PLASTICC) aims to identify promising techniques for obtaining classification probabilities of transient and variable objects by engaging a broader community beyond astronomy. Using mock classification probability submissions emulating realistically complex archetypes of those anticipated of PLASTICC, we compare the sensitivity of two metrics of classification probabilities under various weighting schemes, finding that both yield results that are qualitatively consistent with intuitive notions of classification performance. We thus choose as a metric for PLASTICC a weighted modification of the cross-entropy because it can be meaningfully interpreted in terms of information content. Finally, we propose extensions of our methodology to ever more complex challenge goals and suggest some guiding principles for approaching the choice of a metric of probabilistic data products.
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| 6. |
- Yu, E. Y. W., et al.
(författare)
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The association between coffee consumption and bladder cancer in the bladder cancer epidemiology and nutritional determinants (BLEND) international pooled study
- 2019
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Ingår i: Cancer Causes & Control. - : Springer Science and Business Media LLC. - 0957-5243 .- 1573-7225. ; 30:8, s. 859-870
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundInconsistent results for coffee consumption and bladder cancer (BC) risk have been shown in epidemiological studies. This research aims to increase the understanding of the association between coffee consumption and BC risk by bringing together worldwide case-control studies on this topic.MethodsData were collected from 13 case-control comprising of 5,911 cases and 16,172 controls. Pooled multivariate odds ratios (ORs), with corresponding 95% confidence intervals (CIs), were obtained using multilevel logistic regression models. Furthermore, linear dose-response relationships were examined using fractional polynomial models.ResultsNo association of BC risk was observed with coffee consumption among smokers. However, after adjustment for age, gender, and smoking, the risk was significantly increased for never smokers (ever vs. never coffee consumers: ORmodel2 1.30, 95% CI 1.06-1.59; heavy (>4 cups/day) coffee consumers vs. never coffee consumers: ORmodel2 1.52, 95% CI 1.18-1.97, p trend=0.23). In addition, dose-response analyses, in both the overall population and among never smokers, also showed a significant increased BC risk for coffee consumption of more than four cups per day. Among smokers, a significant increased BC risk was shown only after consumption of more than six cups per day.ConclusionThis research suggests that positive associations between coffee consumption and BC among never smokers but not smokers.
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