Gene set analysis exploiting the topology of a pathway

<p>Abstract</p> <p>Background</p> <p>Recently, a great effort in microarray data analysis is directed towards the study of the so-called gene sets. A gene set is defined by genes that are, somehow, functionally related. For example, genes appearing in a known biological pathway naturally define a gene set. The gene sets are usually identified from a priori biological knowledge. Nowadays, many bioinformatics resources store such kind of knowledge (see, for example, the Kyoto Encyclopedia of Genes and Genomes, among others). Although pathways maps carry important information about the structure of correlation among genes that should not be neglected, the currently available multivariate methods for gene set analysis do not fully exploit it.</p> <p>Results</p> <p>We propose a novel gene set analysis specifically designed for gene sets defined by pathways. Such analysis, based on graphical models, explicitly incorporates the dependence structure among genes highlighted by the topology of pathways. The analysis is designed to be used for overall surveillance of changes in a pathway in different experimental conditions. In fact, under different circumstances, not only the expression of the genes in a pathway, but also the strength of their relations may change. The methods resulting from the proposal allow both to test for variations in the strength of the links, and to properly account for heteroschedasticity in the usual tests for differential expression.</p> <p>Conclusions</p> <p>The use of graphical models allows a deeper look at the components of the pathway that can be tested separately and compared marginally. In this way it is possible to test single components of the pathway and highlight only those involved in its deregulation.</p

Influence of FTO rs9939609 and Mediterranean diet on body composition and weight loss: a randomized clinical trial

Background The Mediterranean diet (MeD) plays a key role in the prevention of obesity. Among the genes involved in obesity, the Fat mass and obesity-associated gene (FTO) is one of the most known, but its interaction with MeD remained uncertain so far. Methods We carried out a study on a sample of 188 Italian subjects, analyzing their FTO rs9939609 alleles, and the difference in body composition between the baseline and a 4-weeks nutritional intervention. The sample was divided into two groups: the control group of 49 subjects, and the MeD group of 139 subjects. Results We found significant relations between MeD and both variation of total body fat (ΔTBFat) (p = 0.00) and gynoid body fat (p = 0.04). ∆TBFat (kg) demonstrated to have a significant relation with the interaction diet-gene (p = 0.04), whereas FTO was associated with the variation of total body water (p = 0.02). Conclusions MeD demonstrated to be a good nutritional treatment to reduce the body fat mass, whereas data about FTO remain uncertain. Confirming or rejecting the hypothesis of FTO and its influence on body tissues during nutritional treatments is fundamental to decide whether its effect has to be taken into consideration during both development of dietetic plans and patients monitoring. Trial Registration ClinicalTrials.gov Id: NCT01890070. Registered 01 July 2013, https://clinicaltrials.gov/ct2/show/NCT0189007

Use of the gamma method for self-contained gene-set analysis of SNP data

Gene-set analysis (GSA) evaluates the overall evidence of association between a phenotype and all genotyped single nucleotide polymorphisms (SNPs) in a set of genes, as opposed to testing for association between a phenotype and each SNP individually. We propose using the Gamma Method (GM) to combine gene-level P-values for assessing the significance of GS association. We performed simulations to compare the GM with several other self-contained GSA strategies, including both one-step and two-step GSA approaches, in a variety of scenarios. We denote a ‘one-step' GSA approach to be one in which all SNPs in a GS are used to derive a test of GS association without consideration of gene-level effects, and a ‘two-step' approach to be one in which all genotyped SNPs in a gene are first used to evaluate association of the phenotype with all measured variation in the gene and then the gene-level tests of association are aggregated to assess the GS association with the phenotype. The simulations suggest that, overall, two-step methods provide higher power than one-step approaches and that combining gene-level P-values using the GM with a soft truncation threshold between 0.05 and 0.20 is a powerful approach for conducting GSA, relative to the competing approaches assessed. We also applied all of the considered GSA methods to data from a pharmacogenomic study of cisplatin, and obtained evidence suggesting that the glutathione metabolism GS is associated with cisplatin drug response

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns

Improved Differential-Linear Attacks with Applications to ARX Ciphers

We present several improvements to the framework of differential-linear attacks with a special focus on ARX ciphers. As a demonstration of their impact, we apply them to Chaskey and ChaCha and we are able to significantly improve upon the best attacks published so far

CMS Data Processing Workflows during an Extended Cosmic Ray Run

Peer reviewe

Aligning the CMS Muon Chambers with the Muon Alignment System during an Extended Cosmic Ray Run

Peer reviewe

Measurements of differential cross-sections in top-quark pair events with a high transverse momentum top quark and limits on beyond the Standard Model contributions to top-quark pair production with the ATLAS detector at √s = 13 TeV

Cross-section measurements of top-quark pair production where the hadronically decaying top quark has transverse momentum greater than 355 GeV and the other top quark decays into ℓνb are presented using 139 fb−1 of data collected by the ATLAS experiment during proton-proton collisions at the LHC. The fiducial cross-section at s = 13 TeV is measured to be σ = 1.267 ± 0.005 ± 0.053 pb, where the uncertainties reflect the limited number of data events and the systematic uncertainties, giving a total uncertainty of 4.2%. The cross-section is measured differentially as a function of variables characterising the tt¯ system and additional radiation in the events. The results are compared with various Monte Carlo generators, including comparisons where the generators are reweighted to match a parton-level calculation at next-to-next-to-leading order. The reweighting improves the agreement between data and theory. The measured distribution of the top-quark transverse momentum is used to search for new physics in the context of the effective field theory framework. No significant deviation from the Standard Model is observed and limits are set on the Wilson coefficients of the dimension-six operators OtG and Otq(8), where the limits on the latter are the most stringent to date. [Figure not available: see fulltext.]

Measurement of the tt¯tt¯ production cross section in pp collisions at √s=13 TeV with the ATLAS detector

A measurement of four-top-quark production using proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the ATLAS detector at the Large Hadron Collider corresponding to an integrated luminosity of 139 fb−1 is presented. Events are selected if they contain a single lepton (electron or muon) or an opposite-sign lepton pair, in association with multiple jets. The events are categorised according to the number of jets and how likely these are to contain b-hadrons. A multivariate technique is then used to discriminate between signal and background events. The measured four-top-quark production cross section is found to be 26+17−15 fb, with a corresponding observed (expected) significance of 1.9 (1.0) standard deviations over the background-only hypothesis. The result is combined with the previous measurement performed by the ATLAS Collaboration in the multilepton final state. The combined four-top-quark production cross section is measured to be 24+7−6 fb, with a corresponding observed (expected) signal significance of 4.7 (2.6) standard deviations over the background-only predictions. It is consistent within 2.0 standard deviations with the Standard Model expectation of 12.0 ± 2.4 fb