Comparative study of gene set enrichment methods

<p>Abstract</p> <p>Background</p> <p>The analysis of high-throughput gene expression data with respect to sets of genes rather than individual genes has many advantages. A variety of methods have been developed for assessing the enrichment of sets of genes with respect to differential expression. In this paper we provide a comparative study of four of these methods: Fisher's exact test, Gene Set Enrichment Analysis (GSEA), Random-Sets (RS), and Gene List Analysis with Prediction Accuracy (GLAPA). The first three methods use associative statistics, while the fourth uses predictive statistics. We first compare all four methods on simulated data sets to verify that Fisher's exact test is markedly worse than the other three approaches. We then validate the other three methods on seven real data sets with known genetic perturbations and then compare the methods on two cancer data sets where our a priori knowledge is limited.</p> <p>Results</p> <p>The simulation study highlights that none of the three method outperforms all others consistently. GSEA and RS are able to detect weak signals of deregulation and they perform differently when genes in a gene set are both differentially up and down regulated. GLAPA is more conservative and large differences between the two phenotypes are required to allow the method to detect differential deregulation in gene sets. This is due to the fact that the enrichment statistic in GLAPA is prediction error which is a stronger criteria than classical two sample statistic as used in RS and GSEA. This was reflected in the analysis on real data sets as GSEA and RS were seen to be significant for particular gene sets while GLAPA was not, suggesting a small effect size. We find that the rank of gene set enrichment induced by GLAPA is more similar to RS than GSEA. More importantly, the rankings of the three methods share significant overlap.</p> <p>Conclusion</p> <p>The three methods considered in our study recover relevant gene sets known to be deregulated in the experimental conditions and pathologies analyzed. There are differences between the three methods and GSEA seems to be more consistent in finding enriched gene sets, although no method uniformly dominates over all data sets. Our analysis highlights the deep difference existing between associative and predictive methods for detecting enrichment and the use of both to better interpret results of pathway analysis. We close with suggestions for users of gene set methods.</p

A comparative study of covariance selection models for the inference of gene regulatory networks

Display Omitted Three different models for inferring gene networks from microarray data are proposed.The most sensitive approach is selected by an exhaustive simulation study.The method reveals a cross-talk between the isoprenoid biosynthesis pathways in Arabidopsis thaliana.The method highlights 9 genes in HRAS signature regulated by the transcription factor RREB1. MotivationThe inference, or 'reverse-engineering', of gene regulatory networks from expression data and the description of the complex dependency structures among genes are open issues in modern molecular biology. ResultsIn this paper we compared three regularized methods of covariance selection for the inference of gene regulatory networks, developed to circumvent the problems raising when the number of observations n is smaller than the number of genes p. The examined approaches provided three alternative estimates of the inverse covariance matrix: (a) the 'PINV' method is based on the Moore-Penrose pseudoinverse, (b) the 'RCM' method performs correlation between regression residuals and (c) '?2C' method maximizes a properly regularized log-likelihood function. Our extensive simulation studies showed that ?2C outperformed the other two methods having the most predictive partial correlation estimates and the highest values of sensitivity to infer conditional dependencies between genes even when a few number of observations was available. The application of this method for inferring gene networks of the isoprenoid biosynthesis pathways in Arabidopsis thaliana allowed to enlighten a negative partial correlation coefficient between the two hubs in the two isoprenoid pathways and, more importantly, provided an evidence of cross-talk between genes in the plastidial and the cytosolic pathways. When applied to gene expression data relative to a signature of HRAS oncogene in human cell cultures, the method revealed 9 genes (p-value<0.0005) directly interacting with HRAS, sharing the same Ras-responsive binding site for the transcription factor RREB1. This result suggests that the transcriptional activation of these genes is mediated by a common transcription factor downstream of Ras signaling. AvailabilitySoftware implementing the methods in the form of Matlab scripts are available at: http://users.ba.cnr.it/issia/iesina18/CovSelModelsCodes.zip

Study of radiation damage and substrate resistivity effects from beam test of silicon microstrip detectors using LHC readout electronics

We present the beam test results of single-sided silicon microstrip detectors, with different substrate resistivities. The effects of radiation damage are studied for a detector irradiated to a fluence of 2.4 multiplied by 10**1**4 n/cm**2. The detectors are read out with the APV6 chip, which is compatible with the 40 MHz LHC clock. The performance of different detectors and readout modes are studied in terms of signal-to-noise ratio and efficiency

Finding New Genes for Non-Syndromic Hearing Loss through an In Silico Prioritization Study

At present, 51 genes are already known to be responsible for Non-Syndromic hereditary Hearing Loss (NSHL), but the knowledge of 121 NSHL-linked chromosomal regions brings to the hypothesis that a number of disease genes have still to be uncovered. To help scientists to find new NSHL genes, we built a gene-scoring system, integrating Gene Ontology, NCBI Gene and Map Viewer databases, which prioritizes the candidate genes according to their probability to cause NSHL. We defined a set of candidates and measured their functional similarity with respect to the disease gene set, computing a score () that relies on the assumption that functionally related genes might contribute to the same (disease) phenotype. A Kolmogorov-Smirnov test, comparing the pair-wise distribution on the disease gene set with the distribution on the remaining human genes, provided a statistical assessment of this assumption. We found at a p-value that the former pair-wise is greater than the latter, justifying a prioritization strategy based on the functional similarity of candidate genes respect to the disease gene set. A cross-validation test measured to what extent the ranking for NSHL is different from a random ordering: adding 15% of the disease genes to the candidate gene set, the ranking of the disease genes in the first eight positions resulted statistically different from a hypergeometric distribution with a p-value and a power. The twenty top-scored genes were finally examined to evaluate their possible involvement in NSHL. We found that half of them are known to be expressed in human inner ear or cochlea and are mainly involved in remodeling and organization of actin formation and maintenance of the cilia and the endocochlear potential. These findings strongly indicate that our metric was able to suggest excellent NSHL candidates to be screened in patients and controls for causative mutations

Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV

Measurements are reported of differential cross sections for the production of a W boson, which decays into a muon and a neutrino, in association with jets, as a function of several variables, including the transverse momenta (pT) and pseudorapidities of the four leading jets, the scalar sum of jet transverse momenta (HT), and the difference in azimuthal angle between the directions of each jet and the muon. The data sample of pp collisions at a centre-of-mass energy of 7 TeV was collected with the CMS detector at the LHC and corresponds to an integrated luminosity of 5.0 fb[superscript −1]. The measured cross sections are compared to predictions from Monte Carlo generators, MadGraph + pythia and sherpa, and to next-to-leading-order calculations from BlackHat + sherpa. The differential cross sections are found to be in agreement with the predictions, apart from the pT distributions of the leading jets at high pT values, the distributions of the HT at high-HT and low jet multiplicity, and the distribution of the difference in azimuthal angle between the leading jet and the muon at low values.United States. Dept. of EnergyNational Science Foundation (U.S.)Alfred P. Sloan Foundatio

Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

Impacts of the Tropical Pacific/Indian Oceans on the Seasonal Cycle of the West African Monsoon

The current consensus is that drought has developed in the Sahel during the second half of the twentieth century as a result of remote effects of oceanic anomalies amplified by local land–atmosphere interactions. This paper focuses on the impacts of oceanic anomalies upon West African climate and specifically aims to identify those from SST anomalies in the Pacific/Indian Oceans during spring and summer seasons, when they were significant. Idealized sensitivity experiments are performed with four atmospheric general circulation models (AGCMs). The prescribed SST patterns used in the AGCMs are based on the leading mode of covariability between SST anomalies over the Pacific/Indian Oceans and summer rainfall over West Africa. The results show that such oceanic anomalies in the Pacific/Indian Ocean lead to a northward shift of an anomalous dry belt from the Gulf of Guinea to the Sahel as the season advances. In the Sahel, the magnitude of rainfall anomalies is comparable to that obtained by other authors using SST anomalies confined to the proximity of the Atlantic Ocean. The mechanism connecting the Pacific/Indian SST anomalies with West African rainfall has a strong seasonal cycle. In spring (May and June), anomalous subsidence develops over both the Maritime Continent and the equatorial Atlantic in response to the enhanced equatorial heating. Precipitation increases over continental West Africa in association with stronger zonal convergence of moisture. In addition, precipitation decreases over the Gulf of Guinea. During the monsoon peak (July and August), the SST anomalies move westward over the equatorial Pacific and the two regions where subsidence occurred earlier in the seasons merge over West Africa. The monsoon weakens and rainfall decreases over the Sahel, especially in August.Peer reviewe

Penilaian Kinerja Keuangan Koperasi di Kabupaten Pelalawan

This paper describe development and financial performance of cooperative in District Pelalawan among 2007 - 2008. Studies on primary and secondary cooperative in 12 sub-districts. Method in this stady use performance measuring of productivity, efficiency, growth, liquidity, and solvability of cooperative. Productivity of cooperative in Pelalawan was highly but efficiency still low. Profit and income were highly, even liquidity of cooperative very high, and solvability was good