EMA - A R package for Easy Microarray data analysis

<p>Abstract</p> <p>Background</p> <p>The increasing number of methodologies and tools currently available to analyse gene expression microarray data can be confusing for non specialist users.</p> <p>Findings</p> <p>Based on the experience of biostatisticians of Institut Curie, we propose both a clear analysis strategy and a selection of tools to investigate microarray gene expression data. The most usual and relevant existing R functions were discussed, validated and gathered in an easy-to-use R package (EMA) devoted to gene expression microarray analysis. These functions were improved for ease of use, enhanced visualisation and better interpretation of results.</p> <p>Conclusions</p> <p>Strategy and tools proposed in the EMA R package could provide a useful starting point for many microarrays users. EMA is part of Comprehensive R Archive Network and is freely available at <url>http://bioinfo.curie.fr/projects/ema/</url>.</p

Should We Abandon the t-Test in the Analysis of Gene Expression Microarray Data: A Comparison of Variance Modeling Strategies

High-throughput post-genomic studies are now routinely and promisingly investigated in biological and biomedical research. The main statistical approach to select genes differentially expressed between two groups is to apply a t-test, which is subject of criticism in the literature. Numerous alternatives have been developed based on different and innovative variance modeling strategies. However, a critical issue is that selecting a different test usually leads to a different gene list. In this context and given the current tendency to apply the t-test, identifying the most efficient approach in practice remains crucial. To provide elements to answer, we conduct a comparison of eight tests representative of variance modeling strategies in gene expression data: Welch's t-test, ANOVA [1], Wilcoxon's test, SAM [2], RVM [3], limma [4], VarMixt [5] and SMVar [6]. Our comparison process relies on four steps (gene list analysis, simulations, spike-in data and re-sampling) to formulate comprehensive and robust conclusions about test performance, in terms of statistical power, false-positive rate, execution time and ease of use. Our results raise concerns about the ability of some methods to control the expected number of false positives at a desirable level. Besides, two tests (limma and VarMixt) show significant improvement compared to the t-test, in particular to deal with small sample sizes. In addition limma presents several practical advantages, so we advocate its application to analyze gene expression data

Prognostic impact of vitamin B6 metabolism in lung cancer

Patients with non-small cell lung cancer (NSCLC) are routinely treated with cytotoxic agents such as cisplatin. Through a genome-wide siRNA-based screen, we identified vitamin B6 metabolism as a central regulator of cisplatin responses in vitro and in vivo. By aggravating a bioenergetic catastrophe that involves the depletion of intracellular glutathione, vitamin B6 exacerbates cisplatin-mediated DNA damage, thus sensitizing a large panel of cancer cell lines to apoptosis. Moreover, vitamin B6 sensitizes cancer cells to apoptosis induction by distinct types of physical and chemical stress, including multiple chemotherapeutics. This effect requires pyridoxal kinase (PDXK), the enzyme that generates the bioactive form of vitamin B6. In line with a general role of vitamin B6 in stress responses, low PDXK expression levels were found to be associated with poor disease outcome in two independent cohorts of patients with NSCLC. These results indicate that PDXK expression levels constitute a biomarker for risk stratification among patients with NSCLC.publishedVersio

Développement d'outils statistiques pour la mise en place de boucles de régulation en microélectronique

En microélectronique, le contrôle des procédés classique n'est plus suffisant pour les nouvelles technologies. Ainsi, un contrôle plus fin du procédé est réalisé à l'aide de boucles de régulation. Cette thèse propose la création et la mise en pratique d'une méthodologie statistique pour la mise en place de boucles de régulation en microélectronique. Cette méthodologie reste générale et peut se transposer aisément à d'autres domaines industriels. Les boucles de régulation nous ont tout d'abord amené à nous interroger sur la fiabilité de la mesure. Nous avons ainsi crée un nouvel indicateur de variabilité de la mesure, appelé capabilité globale, qui s'applique lorsqu'un paramètre est mesuré par plusieurs équipements de métrologie. Une solution opérationnelle a également été proposée par la création et de la mise en production d'un logiciel de calcul de capabilité. Une fois définie la méthodologie de mise en œuvre d'une boucle de régulation, celle-ci est appliquée à un atelier de polissage. Ceci a nécessité une modélisation originale du procédé de fabrication à l'aide du modèle linéaire mixte. Nous avons également comparé et optimisé différents algorithmes de régulation (EWMA, double EWMA, filtre de Kalman...). Pour des raisons évidentes de coût, les différents algorithmes de régulation ne peuvent pas être testés et comparés en production. Nous avons ainsi proposé une simulation du procédé sur la base de données mesurées en production et d'un modèle du procédé. Celle-ci permet de prédire et comparer ce que serait le comportement des algorithmes de régulation en production. Un algorithme optimal a alors été choisi pour l'atelier de polissage.TOULOUSE3-BU Sciences (315552104) / SudocSudocFranceF

Le dépôt de vases dans les tombes en Île-de-France. Une pratique répandue au Moyen Âge

International audienc

SHIPS: Spectral Hierarchical Clustering for the Inference of Population Structure in Genetic Studies

Inferring the structure of populations has many applications for genetic research. In addition to providing information for evolutionary studies, it can be used to account for the bias induced by population stratification in association studies. To this end, many algorithms have been proposed to cluster individuals into genetically homogeneous sub-populations. The parametric algorithms, such as Structure, are very popular but their underlying complexity and their high computational cost led to the development of faster parametric alternatives such as Admixture. Alternatives to these methods are the non-parametric approaches. Among this category, AWclust has proven efficient but fails to properly identify population structure for complex datasets. We present in this article a new clustering algorithm called Spectral Hierarchical clustering for the Inference of Population Structure (SHIPS), based on a divisive hierarchical clustering strategy, allowing a progressive investigation of population structure. This method takes genetic data as input to cluster individuals into homogeneous sub-populations and with the use of the gap statistic estimates the optimal number of such sub-populations. SHIPS was applied to a set of simulated discrete and admixed datasets and to real SNP datasets, that are data from the HapMap and Pan-Asian SNP consortium. The programs Structure, Admixture, AWclust and PCAclust were also investigated in a comparison study. SHIPS and the parametric approach Structure were the most accurate when applied to simulated datasets both in terms of individual assignments and estimation of the correct number of clusters. The analysis of the results on the real datasets highlighted that the clusterings of SHIPS were the more consistent with the population labels or those produced by the Admixture program. The performances of SHIPS when applied to SNP data, along with its relatively low computational cost and its ease of use make this method a promising solution to infer fine-scale genetic patterns

Impact of Prior Bevacizumab Treatment on VEGF-A and PIGF Levels and Outcome Following Second-Line Aflibercept Treatment: Biomarker Post Hoc Analysis of the VELOUR Trial

PURPOSE: Aflibercept is a targeted anti-VEGF therapy used to treat patients with metastatic colorectal cancer (mCRC) following progression on oxaliplatin-based regimens. This post hoc study evaluated the effect of prior bevacizumab treatment and growth factor levels on patient outcomes associated with aflibercept in the VELOUR phase III trial. EXPERIMENTAL DESIGN: Baseline biomarker plasma concentrations were measured using a bead-based multiplex assay. Patients were grouped according to prior bevacizumab treatment, second-line treatment, and serum biomarker concentrations, and analyzed for overall survival (OS) and progression-free survival (PFS). RESULTS: Plasma samples were available for 553 patients (placebo n = 265; aflibercept n = 288), of which 169 had received prior bevacizumab. Nine biomarkers implicated in angiogenesis or bevacizumab resistance correlated with prior bevacizumab therapy. VEGF-A and placental growth factor (PlGF) were the most significantly increased in patients who had received prior bevacizumab compared with those who had not received prior bevacizumab. In the placebo group, patients with high VEGF-A (>144 pg/mL) levels at baseline had worse OS and PFS compared with patients with lower levels at baseline (9.6 vs. 12.9 months). This was also seen in patients who received placebo and had high baseline PlGF (>8 pg/mL; 9.7 vs. 11.7 months). In the aflibercept group, prolonged OS and PFS were observed regardless of baseline VEGF-A or PlGF levels. CONCLUSIONS: High VEGF-A and PlGF serum levels may underlie development of resistance to bevacizumab in patients with mCRC. Aflibercept retains its activity regardless of baseline VEGF-A and PlGF levels and may be an effective second-line treatment for patients with bevacizumab-induced resistance.status: publishe

SMETHILLIUM: spatial normalization METHod for ILLumina InfinIUM HumanMethylation BeadChip

L'auteur GIldas Mazo actuellement à l'INRA - Centre de Jouy-en-Josas - Unité MaIAGEInternational audienceSummary: DNA methylation is a major epigenetic modification in human cells. Illumina HumanMethylation27 BeadChip makes it possible to quantify the methylation state of 27 578 loci spanning 14 495 genes.We developed a non-parametric normalization method to correct the spatial background noise in order to improve the signal-to-noise ratio. The prediction performance of the proposed method was assessed on three fully methylated samples and three fully unmethylated DNA samples. We demonstrate that the spatial normalization outperforms BeadStudio to predict the methylation state of a given locus. Availability and Implementation: A R script and the data are available at the following address: http://bioinfo.curie.fr/projects/ smethillium. Contact: [email protected] Supplementary information: Supplementary data are available at Bioinformatics online

Population history trees used to generate the simulated datasets.

<p>A) one population B) three sub-populations C) five sub-populations D) ten sub-populations E) twenty sub-populations.</p