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Registros recuperados: 13
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Analysis of a simulated microarray dataset : Comparison of methods for data normalisation and detection of differential expression Inra
Watson, M.; Pérez-Alegre, M.; Baron, M.D.; Delmas, C.; Dovc, P.; Duval, M.; Foulley, J.L.; Garrido-Pavon, J.J.; Hulsegge, I.; Jaffrézic, F.; Jiménez-Marin, A.; Lavric, M.; Lê Cao, K.A.; Marot, G.; Mouzaki, D.; Pool, M.H.; Robert-Granié, C.; San Cristobal, M.; Tosser-Klopp, G.; Waddington, D.; Koning, D.J. de.
Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed.Methods of comparing the normalised data are also abundant, and no clear consensus has yetbeen reached. The purpose of this paper was to compare those methods used by the EADGENE network on a very noisy simulated data set. With the a priori knowledge of which genes are differentially expressed, it is possible to compare the success of each approach quantitatively.Use of an intensity-dependent normalisation procedure was common, as was correction formultiple testing. Most variety in performance...
Tipo: Journal Article Palavras-chave: GENE EXPRESSION; STATISTICAL ANALYSIS; SIMULATION; TWO COLOUR MICROARRAY.
Ano: 2007 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD2008dce3eba7&uri=/notices/prodinra1/2011/04/
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Analysis of the real EADGENE data set : Comparison of methods and guidelines for data normalisation and selection of differentially expressed genes Inra
Jaffrézic, F.; Koning, D.J.; Boettcher, P.J.; Bonnet, A.; Buitenhuis, B.; Closset, R.; Déjean, S.; Delmas, C.; Detilleux, J.C.; Dovc, P.; Duval, M.; Foulley, J.L.; Hedegaard, J.; Hornshoj, H.; Hulsegge, I.; Janss, L.; Jensen, K.; Jiang, L.; Lavric, M.; Le Cao, K.A.; Lund, M.S.; Malinverni, R.; Marot, G.; Nie, H.; Petzl, W.; Pool, M.H.; Robert-Granié, C.; San Cristobal, M.; Van Schothorst, E.M.; Schuberth, H.J.; Sorensen, P.; Stella, A.; Tosser-Klopp, G.; Waddington, D.; Watson, M.; Yang, W.; Zerbe, H.; Seyfert, H.M..
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 geneexpression 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...
Tipo: Journal Article Palavras-chave: QUALITY CONTROL; DIFFERENTIALLY EXPRESSED GENES; MASTITIS RESISTANCE; MICROARRAY DATA; NORMALISATION.
Ano: 2007 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD200842dc463c&uri=/notices/prodinra1/2011/04/
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Analysis of the real EADGENE data set : Multivariate approaches and post analysis Inra
Sorensen, P.; Bonnet, A.; Buitenhuis, B.; Closset, R.; Déjean, S.; Delmas, C.; Duval, M.; Glass, L.; Hedegaard, J.; Hornshoj, H.; Hulsegge, I.; Jaffrézic, F.; Jensen, K.; Jiang, L.; Koning, D.J.; Lê Cao, K.A.; Nie, H.; Petzl, W.; Pool, M.H.; Robert-Granié, C.; San Cristobal, M.; Lund, M.S.; Van Schothorst, E.M.; Schuberth, H.J.; Seyfert, H.M.; Tosser-Klopp, G.; Waddington, D.; Watson, M.; Yang, W.; Zerbe, H..
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...
Tipo: Journal Article Palavras-chave: BOVINE ANNOTATION; BOVINE MICROARRAY; GENE SET ANALYSIS; MASTITIS; MULTIVARIATE APPROACHES.
Ano: 2007 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD20087102cb92&uri=/notices/prodinra1/2011/04/
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Character process model for semen volume in AI rams : evaluation of correlation structures for long and short-term environmental effects Inra
David, I.; Bodin, L.; Lagriffoul, G.; Manfredi, E.; Robert-Granié, C..
Tipo: Journal Article Palavras-chave: Serial correlation; Longitudinal data; Semen; Sheep.
Ano: 2007 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD2007b5c10c71&uri=/notices/prodinra1/2009/12/
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Evolution during the productive life and individual variability of milk emission at machine milking in Sardinian x Lacaune back-cross ewes Inra
Casu, S.; Marie-Etancelin, C.; Robert-Granié, C.; Barillet, F.; Carta, A..
Breeders have always been interested in improving the ewes’ milkability, since the milking is the most time-consuming task ofdairy sheep farmers. This work was aimed at studying the evolution during the productive life and the individual variability of milkemission traits at machine milking in sheep. Data were recorded in an experimental flock of 889 Sardinian×Lacaune back-crossewes, by using an automatic device developed by INRA. The analyzed variables (59,615 records) were total milk yield (TMY, ml),machine milk yield (MMY, ml), stripped milk yield (SMY, ml), machine milking time (MMT, s), latency time (LT, s), maximum(MMF) and average (AMF) milk flow (ml/s), collected fortnightly at a.m. and p.m. milking for 4 years. Univariate mixed modelswere used for...
Tipo: Journal Article Palavras-chave: DAIRY SHEEP; MACHINE MILKING ABILITY; MILKING SPEED.
Ano: 2008 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD2008924c7bb1&uri=/notices/prodinra1/2008/06/
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Genetic and environmental effects on semen traits in Lacaune and Manech tête rousse AI rams Inra
David, I.; Druart, X.; Lagriffoul, G.; Manfredi, E.; Robert-Granié, C.; Bodin, L..
Tipo: Journal Article Palavras-chave: Ram; Semen; Environmental factor.
Ano: 2007 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD2007cf9558e8&uri=/notices/prodinra1/2009/12/
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Genetic correlation between female fertility and milk yield in Lacaune Sheep Inra
David, I.; Astruc, J.M; Lagriffoul, G.; Manfredi, E.; Robert-Granié, C.; Bodin, L..
Tipo: Journal Article Palavras-chave: FERTILITE; PRODUCTION LAITIERE; OVIN; CORRELATION GENETIQUE FERTILITY; MILK YIELD; SHEEP; GENETIC CORRELATION.
Ano: 2008 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD2008d236ea30&uri=/notices/prodinra1/2008/11/
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Genetic variability in residual feed intake in rainbow trout clones and testing of indirect selection criteria Inra
Grima, L.; Quillet, E.; Boujard, T.; Robert-Granié, C.; Chatain, B.; Mambrini, M..
Tipo: Journal Article Palavras-chave: RAINBOW TROUT; CLONE; RESIDUAL FEED INTAKE; INDIRECT CRITERIA; SELECTION.
Ano: 2008 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD20084602f9e3&uri=/notices/prodinra1/2009/12/
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Methods for interpreting lists of affected genes obtained in a DNA microarray experiment Inra
Hedegaard, J.; Arce, C.; Bicciato, S.; Bonnet, A.; Buitenhuis, B.; Collado-Romero, M.; Conley, L.N.; San Cristobal, M.; Ferrari, F.; Garrido, J.J.; Groenen, M.A.M.; Hornshoj, H.; Hulsegge, I.; Jiang, L.; Jiménez-Marin, A.; Kommadath, A.; Lagarrigue, S.; Leunissen, J.A.M.; Liaubet, L.; Neerincx, P.B.T.; Nie, H.; Van der Poel, J.; Prickett, D.; Ramirez-Boo, M.; Rebell, J.M.J.; Robert-Granié, C.; Skarman, A.; Smits, M.A.; Sorensen, P.; Tosser-Klopp, G.; Watson, M..
Tipo: Journal Article Palavras-chave: DNA; MICROARRAY; METHODS; CHIKEN; GENONE.
Ano: 2009 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD20106f44f250&uri=/notices/prodinra1/2011/02/
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Pathway results from the chicken data set using GOTM, Pathway studio and ingenuity softwares Inra
Bonnet, A.; Lagarrigue, S.; Liaubet, L.; Robert-Granié, C.; San Cristobal, M.; Tosser-Klopp, G..
Tipo: Journal Article Palavras-chave: GOTM; PATHWAY STUDIO; INGENUITY; SOFTWARES; GENE.
Ano: 2009 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD2009dfa6ec78&uri=/notices/prodinra1/2009/10/
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Performance of genomic selection in mice Inra
Legarra, A.; Robert-Granié, C.; Manfredi, E.; Elsen, J.M..
Tipo: Journal Article Palavras-chave: GENETIC EVOLUTION; SELECTION; LINKAGE DESEQUILIBRIUM; SNP; MARKER ASSISTED.
Ano: 2008 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD20083526791a&uri=/notices/prodinra1/2008/09/
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Predicting qualitative phenotypes from microarray data - the Eadgene pig data set Inra
Robert-Granié, C.; Le Cao, K.A.; San Cristobal, M..
Tipo: Journal Article Palavras-chave: RANDOM FOREST; PLS; SPARSE PLS; MICROARRAY; EADGENE; PIG.
Ano: 2009 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD2009bbc3ef1a&uri=/notices/prodinra1/2009/10/
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Response to somatic cell count-based selection for mastitits resistance in a divergent selection experiment in sheep Inra
Rupp, R.; Bergonier, D.; Dion, S.; Hygonenq, M.C.; Aurel, M.R.; Robert-Granié, C.; Foucras, G..
Tipo: Journal Article Palavras-chave: MASTITIS; SOMATIC CELL COUNT; SCS; DIVERGENT SELECTION; DAIRY SHEEP.
Ano: 2009 URL: http://www.prodinra.inra.fr/prodinra/pinra/doc.xsp?id=PROD2009bb077c0d&uri=/notices/prodinra1/2009/03/
Registros recuperados: 13
Primeira ... 1 ... Última
 

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