Search

Your search keyword '"Dejean Sébastien"' showing total 31 results
Start Over Author "Dejean Sébastien" Search Limiters Available in Library Collection
31 results on '"Dejean Sébastien"'

1. Supervised Multiple Kernel Learning approaches for multi-omics data integration

Author

Briscik, Mitja, Tazza, Gabriele, Dillies, Marie-Agnes, Vidács, László, and Dejean, Sébastien

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Applications
Abstract

Advances in high-throughput technologies have originated an ever-increasing availability of omics datasets. The integration of multiple heterogeneous data sources is currently an issue for biology and bioinformatics. Multiple kernel learning (MKL) has shown to be a flexible and valid approach to consider the diverse nature of multi-omics inputs, despite being an underused tool in genomic data mining. We provide novel MKL approaches based on different kernel fusion strategies. To learn from the meta-kernel of input kernels, we adapted unsupervised integration algorithms for supervised tasks with support vector machines. We also tested deep learning architectures for kernel fusion and classification. The results show that MKL-based models can outperform more complex, state-of-the-art, supervised multi-omics integrative approaches. Multiple kernel learning offers a natural framework for predictive models in multi-omics data. It proved to provide a fast and reliable solution that can compete with and outperform more complex architectures. Our results offer a direction for bio-data mining research, biomarker discovery and further development of methods for heterogeneous data integration.

Published
2024
Full Text
View/download PDF

2. Can we predict QPP? An approach based on multivariate outliers

Author

Chifu, Adrian-Gabriel, Déjean, Sébastien, Garouani, Moncef, Mothe, Josiane, Ortiz, Diégo, and Ullah, Md Zia

Subjects
Computer Science - Information Retrieval, H.3.3
Abstract

Query performance prediction (QPP) aims to forecast the effectiveness of a search engine across a range of queries and documents. While state-of-the-art predictors offer a certain level of precision, their accuracy is not flawless. Prior research has recognized the challenges inherent in QPP but often lacks a thorough qualitative analysis. In this paper, we delve into QPP by examining the factors that influence the predictability of query performance accuracy. We propose the working hypothesis that while some queries are readily predictable, others present significant challenges. By focusing on outliers, we aim to identify the queries that are particularly challenging to predict. To this end, we employ multivariate outlier detection method. Our results demonstrate the effectiveness of this approach in identifying queries on which QPP do not perform well, yielding less reliable predictions. Moreover, we provide evidence that excluding these hard-to-predict queries from the analysis significantly enhances the overall accuracy of QPP.

Published
2024
Full Text
View/download PDF

3. Improvement of variables interpretability in kernel PCA

Author

Briscik, Mitja, Dillies, Marie-Agnès, and Déjean, Sébastien

Subjects
Statistics - Applications
Abstract

Kernel methods have been proven to be a powerful tool for the integration and analysis of highthroughput technologies generated data. Kernels offer a nonlinear version of any linear algorithm solely based on dot products. The kernelized version of Principal Component Analysis is a valid nonlinear alternative to tackle the nonlinearity of biological sample spaces. This paper proposes a novel methodology to obtain a data-driven feature importance based on the KPCA representation of the data. The proposed method, kernel PCA Interpretable Gradient (KPCA-IG), provides a datadriven feature importance that is computationally fast and based solely on linear algebra calculations. It has been compared with existing methods on three benchmark datasets. The accuracy obtained using KPCA-IG selected features is equal to or greater than the other methods' average. Also, the computational complexity required demonstrates the high efficiency of the method. An exhaustive literature search has been conducted on the selected genes from a publicly available Hepatocellular carcinoma dataset to validate the retained features from a biological point of view. The results once again remark on the appropriateness of the computed ranking. The black-box nature of kernel PCA needs new methods to interpret the original features. Our proposed methodology KPCA-IG proved to be a valid alternative to select influential variables in high-dimensional high-throughput datasets, potentially unravelling new biological and medical biomarkers.

Published
2023
Full Text
View/download PDF

4. Professionalization Tools: Impact of the Game-Based Website 'Check Your Smile' on Specialized Terminology Acquisition

Author

Yassine-Diab, Nadia, Hartwell, Laura M., and Dejean, Sébastien

Abstract

Computer assisted vocabulary learning, i.e. specialized terminology acquisition, is a major tool to learning Languages for Specific Purposes (LSP) necessary to students' professionalization. One current area of research is digital game-based language learning because of its motivating qualities. This paper discusses electronics students' acquisition of specific vocabulary as related to the free game-based collaborative platform Check Your Smile (CYS), which is entirely devoted to learning LSP terminology. CYS aggregates various types of games that automatically generate individualized game plays, drawing upon a collaboratively constructed multilingual dictionary. The study focuses on multiple variables including attending a selective engineering course taught in English and the language used to teach the mandatory electronics class. Empirical data shows that students having used CYS tend to obtain better vocabulary test scores than students who did not. [For the complete volume, "CALL and Professionalisation: Short Papers from EUROCALL 2021 (29th, Online, August 26-27, 2021)," see ED616972.]

Published
2021

5. Does probabilistic modelling of linkage disequilibrium evolution improve the accuracy of QTL location in animal pedigree?

Author

Estivals Delphine, Ytournel Florence, Druet Tom, Gilbert Hélène, Legarra Andrés, Dejean Sébastien, Cierco-Ayrolles Christine, Oumouhou Naïma, and Mangin Brigitte

Subjects
Animal culture, SF1-1100, Genetics, QH426-470
Abstract

Abstract Background Since 2001, the use of more and more dense maps has made researchers aware that combining linkage and linkage disequilibrium enhances the feasibility of fine-mapping genes of interest. So, various method types have been derived to include concepts of population genetics in the analyses. One major drawback of many of these methods is their computational cost, which is very significant when many markers are considered. Recent advances in technology, such as SNP genotyping, have made it possible to deal with huge amount of data. Thus the challenge that remains is to find accurate and efficient methods that are not too time consuming. The study reported here specifically focuses on the half-sib family animal design. Our objective was to determine whether modelling of linkage disequilibrium evolution improved the mapping accuracy of a quantitative trait locus of agricultural interest in these populations. We compared two methods of fine-mapping. The first one was an association analysis. In this method, we did not model linkage disequilibrium evolution. Therefore, the modelling of the evolution of linkage disequilibrium was a deterministic process; it was complete at time 0 and remained complete during the following generations. In the second method, the modelling of the evolution of population allele frequencies was derived from a Wright-Fisher model. We simulated a wide range of scenarios adapted to animal populations and compared these two methods for each scenario. Results Our results indicated that the improvement produced by probabilistic modelling of linkage disequilibrium evolution was not significant. Both methods led to similar results concerning the location accuracy of quantitative trait loci which appeared to be mainly improved by using four flanking markers instead of two. Conclusions Therefore, in animal half-sib designs, modelling linkage disequilibrium evolution using a Wright-Fisher model does not significantly improve the accuracy of the QTL location when compared to a simpler method assuming complete and constant linkage between the QTL and the marker alleles. Finally, given the high marker density available nowadays, the simpler method should be preferred as it gives accurate results in a reasonable computing time.

Published
2010
Full Text
View/download PDF

6. Forward and Backward Feature Selection for Query Performance Prediction

Author

Déjean, Sébastien, Ionescu, Radu Tudor, Mothe, Josiane, and Ullah, Md Zia

Subjects
Computer Science - Information Retrieval, Computer Science - Machine Learning, Statistics - Machine Learning
Abstract

The goal of query performance prediction (QPP) is to automatically estimate the effectiveness of a search result for any given query, without relevance judgements. Post-retrieval features have been shown to be more effective for this task while being more expensive to compute than pre-retrieval features. Combining multiple post-retrieval features is even more effective, but state-of-the-art QPP methods are impossible to interpret because of the black-box nature of the employed machine learning models. However, interpretation is useful for understanding the predictive model and providing more answers about its behavior. Moreover, combining many post-retrieval features is not applicable to real-world cases, since the query running time is of utter importance. In this paper, we investigate a new framework for feature selection in which the trained model explains well the prediction. We introduce a step-wise (forward and backward) model selection approach where different subsets of query features are used to fit different models from which the system selects the best one. We evaluate our approach on four TREC collections using standard QPP features. We also develop two QPP features to address the issue of query-drift in the query feedback setting. We found that: (1) our model based on a limited number of selected features is as good as more complex models for QPP and better than non-selective models; (2) our model is more efficient than complex models during inference time since it requires fewer features; (3) the predictive model is readable and understandable; and (4) one of our new QPP features is consistently selected across different collections, proving its usefulness., Comment: Accepted at SAC 2020

Published
2019

9. Non-convex Regularizations for Feature Selection in Ranking With Sparse SVM

Author

Laporte, Léa, Flamary, Rémi, Canu, Stephane, Déjean, Sébastien, and Mothe, Josiane

Subjects
Computer Science - Learning
Abstract

Feature selection in learning to rank has recently emerged as a crucial issue. Whereas several preprocessing approaches have been proposed, only a few works have been focused on integrating the feature selection into the learning process. In this work, we propose a general framework for feature selection in learning to rank using SVM with a sparse regularization term. We investigate both classical convex regularizations such as $\ell\_1$ or weighted $\ell\_1$ and non-convex regularization terms such as log penalty, Minimax Concave Penalty (MCP) or $\ell\_p$ pseudo norm with $p\textless{}1$. Two algorithms are proposed, first an accelerated proximal approach for solving the convex problems, second a reweighted $\ell\_1$ scheme to address the non-convex regularizations. We conduct intensive experiments on nine datasets from Letor 3.0 and Letor 4.0 corpora. Numerical results show that the use of non-convex regularizations we propose leads to more sparsity in the resulting models while prediction performance is preserved. The number of features is decreased by up to a factor of six compared to the $\ell\_1$ regularization. In addition, the software is publicly available on the web.

Published
2015
Full Text
View/download PDF

10. Atrial Natriuretic Peptide Orchestrates a Coordinated Physiological Response to Fuel Non-shivering Thermogenesis

Author

Carper, Deborah, Coué, Marine, Nascimento, Emmani B.M., Barquissau, Valentin, Lagarde, Damien, Pestourie, Carine, Laurens, Claire, Petit, Justine Vily, Soty, Maud, Monbrun, Laurent, Marques, Marie-Adeline, Jeanson, Yannick, Sainte-Marie, Yannis, Mairal, Aline, Déjean, Sébastien, Tavernier, Geneviève, Viguerie, Nathalie, Bourlier, Virginie, Lezoualc’h, Frank, Carrière, Audrey, Saris, Wim H.M., Astrup, Arne, Casteilla, Louis, Mithieux, Gilles, van Marken Lichtenbelt, Wouter, Langin, Dominique, Schrauwen, Patrick, and Moro, Cedric

Published
2020
Full Text
View/download PDF

13. First-in-man Phase 1 Clinical Trial of Gene Therapy for Advanced Pancreatic Cancer: Safety, Biodistribution, and Preliminary Clinical Findings

Author

Buscail, Louis, Bournet, Barbara, Vernejoul, Fabienne, Cambois, Gilles, Lulka, Hubert, Hanoun, Naïma, Dufresne, Marlène, Meulle, Aline, Vignolle-Vidoni, Alix, Ligat, Laetitia, Saint-Laurent, Nathalie, Pont, Frédéric, Dejean, Sébastien, Gayral, Marion, Martins, Frédéric, Torrisani, Jérôme, Barbey, Odile, Gross, Fabian, Guimbaud, Rosine, Otal, Philippe, Lopez, Frédéric, Tiraby, Gérard, and Cordelier, Pierre

Published
2015
Full Text
View/download PDF

15. ASTERICS: A Tool for the ExploRation and Integration of omiCS data

Author

Maigné, Élise, Noirot, Céline, Mariette, Jérôme, Kesewaah, Yaa, Dejean, Sébastien, Guilmineau, Camille, Henry, Julien, Krebs, Arielle, Liaubet, Laurence, Mathevet, Fanny, Hyphen-Stat, Entreprise, Gaspin, Christine, Vialaneix, Nathalie, Vialaneix, Nathalie, Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRAE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Bio-Informatique - Génotoul, Plateforme de Biostatistique (Genotoul Biostat), Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse Capitole (UT Capitole), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Inria, INRAE, Université de Toulouse (UT)-Université de Toulouse (UT)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Unité de Mathématiques et Informatique Appliquées de Toulouse (MIAT INRAE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-BioInfOmics, Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT)-Université de Toulouse (UT)-École nationale supérieure agronomique de Toulouse (ENSAT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Région Occitanie (Grant 20008788 – ASTERICS)

Subjects
[STAT.AP]Statistics [stat]/Applications [stat.AP], [SDV.BA.MVSA]Life Sciences [q-bio]/Animal biology/Veterinary medicine and animal Health, [STAT.AP] Statistics [stat]/Applications [stat.AP], [SDV.BA.MVSA] Life Sciences [q-bio]/Animal biology/Veterinary medicine and animal Health, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

International audience

Published
2022

16. Gene Expression Signature Associated with Clinical Outcome in ALK-Positive Anaplastic Large Cell Lymphoma

Author

Daugrois, Camille, primary, Bessiere, Chloé, additional, Dejean, Sébastien, additional, Anton-Leberre, Véronique, additional, Commes, Thérèse, additional, Pyronnet, Stephane, additional, Brousset, Pierre, additional, Espinos, Estelle, additional, Brugiere, Laurence, additional, Meggetto, Fabienne, additional, and Lamant, Laurence, additional

Published
2021
Full Text
View/download PDF

19. The antibody response induced FMDV vaccines in sheep correlates with early transcriptomic responses in blood

Author

Jouneau, Luc, Lefebvre, David J., Costa, Fleur, Romey, Aurore, Blaise-Boisseau, Sandra, Relmy, Anthony, Jaszczyszyn, Yan, Dard-Dascot, Cloelia, Dejean, Sébastien, Versillé, Nicolas, Guitton, Edouard, Hudelet, Pascal, Curet, Marianne, De Clercq, Kris, Bakkali-Kassimi, Labib, Zientara, Stephan, Klonjkowski, Bernard, Schwartz-Cornil, Isabelle, Virologie et Immunologie Moléculaires (VIM (UR 0892)), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Saclay-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Virologie UMR1161 (VIRO), École nationale vétérinaire - Alfort (ENVA)-Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université Paris-Est (UPE), Institut de Biologie Intégrative de la Cellule (I2BC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Société d'Exploitation de Produits pour les Industries Chimiques (SEPPIC), Plateforme d'Infectiologie Expérimentale (PFIE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Mérial [Lyon], Mérial, US-Department of Agriculture, Agricultural Research Service, North East Area, Plum Island Animal Disease Center, NY, USA 58-3K95-1658M, Belgian Federal Public Service for Health, Food Chain Safety and Environment RI14/2-26, ANR-14-ANWA-0007,TRANSCRIPTOVAC,Host response gene signatures associated with FMDV infection, vaccination and persistence.(2014), Service for Exotic Viruses and Particular Diseases, Scientific Direction of Infectious Diseases in Animals, École nationale vétérinaire d'Alfort (ENVA)-Agence nationale de sécurité sanitaire de l'alimentation, de l'environnement et du travail (ANSES)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), and Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)

Subjects
lcsh:Immunologic diseases. Allergy, Inactivated vaccines, [SDV.BA.MVSA]Life Sciences [q-bio]/Animal biology/Veterinary medicine and animal Health, Live attenuated vaccines, [SDV]Life Sciences [q-bio], animal diseases, viruses, biochemical phenomena, metabolism, and nutrition, lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens, lcsh:RC254-282, Article, Viral infection, Adjuvants, [SDV.IMM.VAC]Life Sciences [q-bio]/Immunology/Vaccinology, lcsh:RC581-607
Abstract

Foot and mouth disease (FMD) is a highly contagious viral disease with high economic impact, representing a major threat for cloven-hooved mammals worldwide. Vaccines based on adjuvanted inactivated virus (iFMDV) induce effective protective immunity implicating antibody (Ab) responses. To reduce the biosafety constraints of the manufacturing process, a non-replicative human adenovirus type 5 vector encoding FMDV antigens (Ad5-FMDV) has been developed. Here we compared the immunogenicity of iFMDV and Ad5-FMDV with and without the ISA206VG emulsion-type adjuvant in sheep. Contrasted Ab responses were obtained: iFMDV induced the highest Ab levels, Ad5-FMDV the lowest ones, and ISA206VG increased the Ad5-FMDV-induced Ab responses to protective levels. Each vaccine generated heterogeneous Ab responses, with high and low responders, the latter being considered as obstacles to vaccine effectiveness. A transcriptomic study on total blood responses at 24 h post-vaccination revealed several blood gene module activities correlating with long-term Ab responses. Downmodulation of T cell modules’ activities correlated with high responses to iFMDV and to Ad5-FMDV+ISA206VG vaccines as also found in other systems vaccinology studies in humans and sheep. The impact of cell cycle activity depended on the vaccine types, as it positively correlated with higher responses to iFMDV but negatively to non-adjuvanted Ad5-FMDV. Finally an elevated B cell activity at 24 h correlated with high Ab responses to the Ad5-FMDV+ISA206VG vaccine. This study provides insights into the early mechanisms driving the Ab response induced by different vaccine regimens including Ad5 vectors and points to T cell modules as early biomarker candidates of different vaccine-type efficacy across species., Foot and mouth disease virus: correlates of protection Foot and mouth disease virus (FMDV) is a serious pathogen of cloven hoofed mammals and is of high economic and veterinary importance. Inactivated vaccine (iFMDV) is effective but difficult to produce because of high biosafety level requirements; non-replicating adenovirus vectors carrying key FMDV antigens (Ad5-FMDV) might therefore represent an attractive alternative. Isabelle Schwartz-Cornil and colleagues use sheep to systematically compare vaccination with adjuvanted iFMDV, adjuvanted Ad5-FMDV, or non-adjuvanted Ad5-FMDV. All vaccines produce neutralizing antibody responses which are stable to at least one year, however the iFMDV group elicits the strongest response, followed by the adjuvanted Ad5-FMDV. Ad5-FMDV alone produces weak antibody titers. Blood transcriptomic analysis performed in the first 24 h following vaccination identifies a reduced T cell gene expression module as a correlate of high neutralizing antibody titers. Blood gene expression might therefore offer insights into the mechanistic underpinnings of humoral immunity as well as provide useful biomarker correlates of protection.

Published
2019
Full Text
View/download PDF

20. The Transcriptional Coactivator Peroxisome Proliferator–Activated Receptor (PPAR)γ Coactivator-1α and the Nuclear Receptor PPARα Control the Expression of Glycerol Kinase and Metabolism Genes Independently of PPARγ Activation in Human White Adipocytes

Author

Mazzucotelli, Anne, Viguerie, Nathalie, Tiraby, Claire, Annicotte, Jean-Sébastien, Mairal, Aline, Klimcakova, Eva, Lepin, Emmanuelle, Delmar, Paul, Dejean, Sébastien, Tavernier, Geneviève, Lefort, Corinne, Hidalgo, Juan, Pineau, Thierry, Fajas, Lluis, Clément, Karine, and Langin, Dominique

Published
2007

22. Tweet Data Mining: the Cultural Microblog Contextualization Data Set

Author

Chaham, Yassine Rkha, Scohy, Clémentine, Dejean, Sébastien, Mothe, Josiane, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - INPT (FRANCE), Institut National des Sciences Appliquées de Toulouse - INSA (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), Institut de Mathématiques de Toulouse - IMT (Toulouse, France), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT), Institut de Mathématiques de Toulouse UMR5219 (IMT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Systèmes d’Informations Généralisées (IRIT-SIG), Institut de recherche en informatique de Toulouse (IRIT), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), École supérieure du professorat et de l'éducation - Toulouse Midi-Pyrénées (ESPE Toulouse), Université de Toulouse (UT)-Université de Toulouse (UT), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Institut National des Sciences Appliquées (INSA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), and Université Fédérale Toulouse Midi-Pyrénées

Subjects
Cultural microblog contextualization, Théorie de l'information, [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL, Tweet mining, Recherche d'information, Descriptive analysis, SIGEVI
Abstract

International audience; This paper presents an overview of the data set that was used for the Cultural Microblog Contextualization Workshop at CLEF 2016 and more specifically for the task 1: tweet contextualization. In this paper we first present a descriptive analysis of the data: we consider the variables or features associated with the tweets and analyse them. Then we also analyse the tweet textual content. The results of this work correspond to a first step toward data quality checking. It can also useful in order to understand better the data and its usefulness for some tasks or case studies.

Published
2016

23. Long non-coding RNA expression profile in cytogenetically normal acute myeloid leukemia identifies a distinct signature and a new biomarker in NPM1-mutated patients

Author

De Clara, Etienne, primary, Gourvest, Morgane, additional, Ma, Hanjing, additional, Vergez, François, additional, Tosolini, Marie, additional, Dejean, Sébastien, additional, Demur, Cécile, additional, Delabesse, Eric, additional, Recher, Christian, additional, Touriol, Christian, additional, Martelli, Maria Paola, additional, Falini, Brunangelo, additional, Brousset, Pierre, additional, and Bousquet, Marina, additional

Published
2017
Full Text
View/download PDF

24. Some statistical questions raised by a particular RNAseq study

Author

San Cristobal, Magali, Sarot, Emeline, Labourdette, Delphine, LAMARRE, Sophie, Pyronnet, Stéphane, Dejean, Sébastien, Génétique Physiologie et Systèmes d'Elevage (GenPhySE ), École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, Centre de Recherches en Cancérologie de Toulouse (CRCT), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Ingénierie des Systèmes Biologiques et des Procédés (LISBP), Institut National de la Recherche Agronomique (INRA)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS), Institut de Mathématiques de Toulouse UMR5219 (IMT), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-École nationale supérieure agronomique de Toulouse (ENSAT), Université de Toulouse (UT)-Université de Toulouse (UT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), and Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDV]Life Sciences [q-bio], [SDV.IDA]Life Sciences [q-bio]/Food engineering, [INFO]Computer Science [cs], [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering, statistique, RNA-seq, bioinformatique, ComputingMilieux_MISCELLANEOUS
Abstract

National audience

Published
2014

25. Abstract A27: Long noncoding RNA expression in cytogenetically normal acute myeloid leukemia identifies a distinct signature associated with NPM1 mutations

Author

Clara, Etienne De, primary, Ma, Hanjing, additional, Vergez, François, additional, Quelen, Cathy, additional, Dejean, Sébastien, additional, Demur, Cécile, additional, Delabesse, Eric, additional, Recher, Christian, additional, Touriol, Christian, additional, Martelli, Maria Paola, additional, Falini, Brunangelo, additional, Brousset, Pierre, additional, and Bousquet, Marina, additional

Published
2016
Full Text
View/download PDF

26. Performance Analysis of Information Retrieval Systems

Author

Ayter, Juli, Desclaux, Cecile, Chifu, Adrian-Gabriel, Dejean, Sébastien, Mothe, Josiane, Centre National de la Recherche Scientifique - CNRS (FRANCE), Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE), Institut National des Sciences Appliquées de Toulouse - INSA (FRANCE), Université Toulouse III - Paul Sabatier - UT3 (FRANCE), Université Toulouse - Jean Jaurès - UT2J (FRANCE), Université Toulouse 1 Capitole - UT1 (FRANCE), Institut de Recherche en Informatique de Toulouse - IRIT (Toulouse, France), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA), Systèmes d’Informations Généralisées (IRIT-SIG), Institut de recherche en informatique de Toulouse (IRIT), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées, Institut de Mathématiques de Toulouse UMR5219 (IMT), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Institut National Polytechnique de Toulouse - INPT (FRANCE), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT), Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Toulouse Mind & Brain Institut (TMBI), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université Toulouse Capitole (UT Capitole), Université de Toulouse (UT), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université Toulouse - Jean Jaurès (UT2J), and Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Optimization, Théorie de l'information, Adaptive information retrieval, [INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT], [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR], InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL, InformationSystems_DATABASEMANAGEMENT, Information retrieval, Recherche d'information, Query difficulty, Classification, Random forest
Abstract

International audience; It has been shown that there is not a best information retrieval system configuration which would work for any query, but rather that performance can vary from one query to another. It would be interesting if a meta-system could decide which system should process a new query by learning from the context of previously submitted queries. This paper reports a deep analysis considering more than 80,000 search engine configurations applied to 100 queries and the corresponding performance. The goal of the analysis is to identify which search engine configuration responds best to a certain type of query. We considered two approaches to define query types: one is based on query clustering according to the query performance (their difficulty), while the other approach uses various query features (including query difficulty predictors) to cluster queries. We identified two parameters that should be optimized first. An important outcome is that we could not obtain strong conclusive results; considering the large number of systems and methods we used, this result could lead to the conclusion that current query features does not fit the optimizing problem.

Published
2014

27. Pancreatic preneoplastic lesions plasma signatures and biomarkers based on proteome profiling of mouse models.

Author

Ligat, Laetitia, Saint-Laurent, Nathalie, El-Mrani, Aïcha, Gigoux, Véronique, Al Saati, Talal, Tomasini, Richard, Nigri, Jérémy, Dejean, Sébastien, Pont, Frédéric, Baer, Romain, Guillermet-Guibert, Julie, Cordelier, Pierre, Lopez, Frédéric, Dufresne, Marlène, El-Mrani, Aïcha, Gigoux, Véronique, Nigri, Jérémy, Dejean, Sébastien, Pont, Frédéric, and Lopez, Frédéric

Subjects
PROTEIN analysis, PEPTIDE analysis, ANIMAL experimentation, BIOLOGICAL models, MICE, PANCREATIC tumors, PEPTIDES, PRECANCEROUS conditions, PROTEINS, PROTEOMICS, CARCINOMA in situ, DUCTAL carcinoma, PROTEIN microarrays
Abstract

Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies with a mortality that is almost identical to incidence. Because early detected PDAC is potentially curable, blood-based biomarkers that could detect currently developing neoplasia would improve patient survival and management. PDAC develops from pancreatic intraepithelial neoplasia (PanIN) lesions, graded from low grade (PanIN1) to high grade (PanIN3). We made the hypothesis that specific proteomic signatures from each precancerous stage exist and are detectable in plasma.Methods: We explored the peptide profiles of microdissected PanIN cells and of plasma samples corresponding to the different PanIN grade from genetically engineered mouse models of PDAC using capillary electrophoresis coupled to mass spectrometry (CE-MS) and Chip-MS/MS.Results: We successfully characterised differential peptides profiles from PanIN microdissected cells. We found that plasma from tumor-bearing mice and age-matched controls exhibit discriminative peptide signatures. We also determined plasma peptide signatures corresponding to low- and high-grade precancerous step present in the mice pancreas using the two mass spectrometry technologies. Importantly, we identified biomarkers specific of PanIN3.Conclusions: We demonstrate that benign and advanced PanIN lesions display distinct plasma peptide patterns. This strongly supports the perspectives of developing a non-invasive screening test for prediction and early detection of PDAC. [ABSTRACT FROM AUTHOR]

Published
2015
Full Text
View/download PDF

28. The transcriptional coactivator peroxisome proliferator activated receptor (PPAR)gamma coactivator-1 alpha and the nuclear receptor PPAR alpha control the expression of glycerol kinase and metabolism genes independently of PPAR gamma activation in human white adipocytes

Author

Mazzucotelli, Anne, Viguerie, Nathalie, Tiraby, Claire, Annicotte, Jean-Sébastien, Mairal, Aline, Klimcáková, Eva, Lepin, Emmanuelle, Delmar, Paul, Dejean, Sébastien, Tavernier, Geneviève, Lefort, Corinne, Hidalgo, Juan, Pineau, Thierry, Fajas, Lluis, Clément, Karine, Langin, Dominique, Laboratoire de Biochimie [Purpan], Université Toulouse III - Paul Sabatier ( UPS ), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut Fédératif de Biologie (IFB) - Hôpital Purpan, Hôpital Purpan [Toulouse], CHU Toulouse [Toulouse]-CHU Toulouse [Toulouse]-Hôpital Purpan [Toulouse], CHU Toulouse [Toulouse], Institut de médecine moléculaire de Rangueil ( I2MR ), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-IFR150-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Franco-Czech Laboratory for Clinical Research on Obesity, Charles University [Prague]-Institut National de la Santé et de la Recherche Médicale ( INSERM ), Métabolisme et cancer, Université Montpellier 1 ( UM1 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Mathématiques Appliquées aux Systèmes - EA 4037 ( MAS ), Ecole Centrale Paris, Statistics and Probality Laboratory, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique ( CNRS ), Institute of Neurosciences, University of Barcelona, Pharmacology and Toxicology Laboratory, Institut National de la Recherche Agronomique ( INRA ), Centre de Recherche des Cordeliers ( CRC (UMR_S 872) ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire de Biochimie [CHU Toulouse], Institut Fédératif de Biologie (IFB), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Pôle Biologie [CHU Toulouse], Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Institut de médecine moléculaire de Rangueil (I2MR), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)- Institut Fédératif de Recherche Bio-médicale Institution (IFR150)-Institut National de la Santé et de la Recherche Médicale (INSERM), Charles University [Prague] (CU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM), Mathématiques Appliquées aux Systèmes - EA 4037 (MAS), Laboratoire de Statistique et Probabilités (LSP), Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Institut National des Sciences Appliquées (INSA)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Agronomique (INRA), Centre de Recherche des Cordeliers (CRC (UMR_S 872)), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées- Institut Fédératif de Recherche Bio-médicale Institution (IFR150)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Institut National des Sciences Appliquées (INSA)-Université Fédérale Toulouse Midi-Pyrénées-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Simon, Marie Francoise, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-IFR150-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS), Université Paris Descartes - Paris 5 (UPD5)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Charles University [Prague]-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Enzymologic, MESH : PPAR gamma, [SDV]Life Sciences [q-bio], Nuclear Receptor Coactivators, MESH : PPAR alpha, MESH : Adipocytes, Gene Expression Regulation, Enzymologic, MESH : Gene Expression Regulation, Enzymologic, MESH : Intracellular Signaling Peptides and Proteins, Glycerol Kinase, MESH: Intracellular Signaling Peptides and Proteins, Adipocytes, Humans, PPAR alpha, MESH: PPAR alpha, MESH: Adipocytes, MESH : Glycerol Kinase, MESH: Humans, MESH : Gene Expression Regulation, MESH: Gene Expression Regulation, Enzymologic, MESH: Glycerol Kinase, MESH : Humans, Intracellular Signaling Peptides and Proteins, MESH: Gene Expression Regulation, [SDV] Life Sciences [q-bio], PPAR gamma, Gene Expression Regulation, MESH: PPAR gamma
Abstract

International audience; OBJECTIVE: The purpose of this work was to determine the pattern of genes regulated by peroxisome proliferator-activated receptor (PPAR) gamma coactivator 1 alpha (PGC-1 alpha) in human adipocytes and the involvement of PPARalpha and PPARgamma in PGC-1 alpha transcriptional action. RESEARCH DESIGN AND METHODS: Primary cultures of human adipocytes were transduced with a PGC-1 alpha adenovirus and treated with PPARgamma and PPARalpha agonists. Variation in gene expression was assessed using pangenomic microarrays and quantitative RT-PCR. To investigate glycerol kinase (GyK), a target of PGC-1 alpha, we measured enzymatic activity and glycerol incorporation into triglycerides. In vivo studies were performed on wild-type and PPARalpha(-/-) mice. The GyK promoter was studied using chromatin immunoprecipitation and promoter reporter gene assays. RESULTS: Among the large number of genes regulated by PGC-1 alpha independently of PPARgamma, new targets involved in metabolism included the gene encoding GyK. The induction of GyK by PGC-1 alpha was observed at the levels of mRNA, enzymatic activity, and glycerol incorporation into triglycerides. PPARalpha was also upregulated by PGC-1 alpha. Its activation led to an increase in GyK expression and activity. PPARalpha was shown to bind and activate the GyK promoter. Experiments in mice confirmed the role of PGC-1 alpha and PPARalpha in the regulation of GyK in vivo. CONCLUSIONS: This work uncovers novel pathways regulated by PGC-1 alpha and reveals that PPARalpha controls gene expression in human white adipocytes. The induction of GyK by PGC-1 alpha and PPARalpha may promote a futile cycle of triglyceride hydrolysis and fatty acid reesterification.

Published
2007
Full Text
View/download PDF

30. Analysis of the real EADGENE data set: Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes (Open Access publication)

Author

Sørensen Peter, Schuberth Hans-Joachim, van Schothorst Evert M, San Cristobal Magali, Robert-Granié Christèle, Pool Marco H, Petzl Wolfram, Nie Haisheng, Marot Guillemette, Malinverni Roberto, Lund Mogens, Cao Kim-Anh, Lavrič Miha, Jiang Li, Jensen Kirsty, Janss Luc, Hulsegge Ina, Hornshøj Henrik, Hedegaard Jakob, Foulley Jean-Louis, Duval Mylène, Dovč Peter, Detilleux Johanne C, Delmas Céline, Déjean Sébastien, Closset Rodrigue, Buitenhuis Bart, Bonnet Agnès, Boettcher Paul J, de Koning Dirk-Jan, Jaffrézic Florence, Stella Alessandra, Tosser-Klopp Gwenola, Waddington David, Watson Michael, Yang Wei, Zerbe Holm, and Seyfert Hans-Martin

Subjects
quality control, differentially expressed genes, mastitis resistance, microarray data, normalisation, Animal culture, SF1-1100, Genetics, QH426-470
Abstract

Abstract A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in order to provide some more general data analysis guidelines. All the workshop participants were given a real data set obtained in an EADGENE funded microarray study looking at the gene expression changes following artificial infection with two different mastitis causing bacteria: Escherichia coli and Staphylococcus aureus. It was reassuring to see that most of the teams found the same main biological results. In fact, most of the differentially expressed genes were found for infection by E. coli between uninfected and 24 h challenged udder quarters. Very little transcriptional variation was observed for the bacteria S. aureus. Lists of differentially expressed genes found by the different research teams were, however, quite dependent on the method used, especially concerning the data quality control step. These analyses also emphasised a biological problem of cross-talk between infected and uninfected quarters which will have to be dealt with for further microarray studies.

Published
2007
Full Text
View/download PDF

31. Analysis of the real EADGENE data set: Multivariate approaches and post analysis (Open Access publication)

Author

Schuberth Hans-Joachim, van Schothorst Evert M, Lund Mogens, San Cristobal Magali, Robert-Granié Christèle, Pool Marco H, Petzl Wolfram, Nie Haisheng, Cao Kim-Anh, de Koning Dirk-Jan, Jiang Li, Jensen Kirsty, Hulsegge Ina, Jaffrézic Florence, Hornshøj Henrik, Hedegaard Jakob, Glass Liz, Duval Mylène, Delmas Céline, Déjean Sébastien, Closset Rodrigue, Buitenhuis Bart, Bonnet Agnès, Sørensen Peter, Seyfert Hans-Martin, Tosser-Klopp Gwenola, Waddington David, Watson Michael, Yang Wei, and Zerbe Holm

Subjects
bovine annotation, bovine microarray, gene set analysis, mastitis, multivariate approaches, Animal culture, SF1-1100, Genetics, QH426-470
Abstract

Abstract The aim of this paper was to describe, and when possible compare, the multivariate methods used by the participants in the EADGENE WP1.4 workshop. The first approach was for class discovery and class prediction using evidence from the data at hand. Several teams used hierarchical clustering (HC) or principal component analysis (PCA) to identify groups of differentially expressed genes with a similar expression pattern over time points and infective agent (E. coli or S. aureus). The main result from these analyses was that HC and PCA were able to separate tissue samples taken at 24 h following E. coli infection from the other samples. The second approach identified groups of differentially co-expressed genes, by identifying clusters of genes highly correlated when animals were infected with E. coli but not correlated more than expected by chance when the infective pathogen was S. aureus. The third approach looked at differential expression of predefined gene sets. Gene sets were defined based on information retrieved from biological databases such as Gene Ontology. Based on these annotation sources the teams used either the GlobalTest or the Fisher exact test to identify differentially expressed gene sets. The main result from these analyses was that gene sets involved in immune defence responses were differentially expressed.

Published
2007
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results