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Génétique Quantitative et Évolution - Le Moulon

Tristan MARY-HUARD

Tristan MARY-HUARD

Junior Investigator, INRAE

Statistical methods for quantitative genetics

tristan.mary-huard@agroparistech.fr

+33 (0)1 69 33 23 58

orcid.org/0000-0002-3839-9067

Publications

  • Génétique Quantitative et Évolution - Le Moulon
  • Université Paris-Saclay, INRAE, CNRS, AgroParisTech
  • Ferme du Moulon
  • F-91190 Gif-sur-Yvette

Positions and Education

  • Current: Researcher at INRA, GQE-Le Moulon and MIA Paris
  • 2007-2012: Associate professor in statistics at AgroParisTech
  • 2017: HDR Some contributions to statistical modeling and model selection with applications to genomics and quantitative genetics, Univ. Paris-Sud, 2017
  • 2006: PhD Dimension reduction and model selection for supervised classification, MIA Paris, Univ. Paris-Sud
  • 1998-2001: National School of Statistics and Data Analysis (ENSAI)

Research Interests

In statistics:

  • Model selection in classification and regression
  • Variable aggregation, variable selection
  • Latent variable models and Mixed models
  • Breakpoint detection

In genomics:

  • Data integration for multi-omics
  • Gene expression/methylation analysis

In quantitative/population genetics:

  • QTL detection
  • Genomic selection
  • Fst estimation

Teaching

  • Classification en grande dimension (avec C. Giraud), M2 Mathématiques pour les Sciences du Vivant (Univ. Paris Sud 11).
  • Statistique pour la génétique, (avec T. Van Dooren and ML. Martin-Magniette), M1 Sciences de la vie (ENS Paris).
  • Modèle linéaire pour l’ingénieur, (avec P. Barbillon), eq. M1 (IFP School).

Book and book chapters :

  • Le modèle linéaire et ses extensions, 2015, Ed. Ellipses (with L. Bel, JJ Daudin, M. Etienne, E. Lebarbier, T. Mary-Huard, S. Robin, C. Vuillet)
  • Introduction to Statistical Methods for Complex Systems, in Handbook of Statistical Systems Biology, 2011, John Wiley & Sons (with S. Robin)
  • Introduction to Statistical Methods for Microarray Data Analysis, in Mathematical and Computational Methods in Biology, 2006, Ed. Hermann: Paris (with F. Picard, S. Robin)

Selected publications

Rio S, Mary-Huard T, Moreau L, Charcosset A. (2019) Genomic selection efficiency and a priori estimation of accuracy in a structured dent maize panel. Theor Appl Genet, 1 (132) 81-96
Celisse A, Mary-Huard T. (2018) Theoretical Analysis of Cross-Validation for Estimating the Risk of the $k$-Nearest Neighbor Classifier. Journal of Machine Learning Research, 58 (19) 1-54
Brandenburg JT, Mary-Huard T, Rigaill G, Hearne SJ, Corti H, Joets J, Vitte C, Charcosset A, Nicolas SD, Tenaillon MI. (2017) Independent introductions and admixtures have contributed to adaptation of European maize and its American counterparts. PLOS Genetics, 3 (13) e1006666
Laporte F, Charcosset A, Mary‐Huard T. (2017) Estimation of the relatedness coefficients from biallelic markers, application in plant mating designs. Biometrics, 3 (73) 885-894
Delatola EI, Lebarbier E, Mary-Huard T, Radvanyi F, Robin S, Wong J. (2017) SegCorr a statistical procedure for the detection of genomic regions of correlated expression. BMC Bioinformatics, 1 (18) 333
Roux F, Mary-Huard T, Barillot E, Wenes E, Botran L, Durand S, Villoutreix R, Martin-Magniette ML, Camilleri C, Budar F. (2016) Cytonuclear interactions affect adaptive traits of the annual plant Arabidopsis thaliana in the field. Proceedings of the National Academy of Sciences of the United States of America, 13 (113) 3687-92

Publications

  • Arca M., Mary-Huard T. , Gouesnard B., Bérard A., Bauland C., Combes V., Madur D., Charcosset A., Nicolas SD.. (2021) Deciphering the Genetic Diversity of Landraces With High-Throughput SNP Genotyping of DNA Bulks: Methodology and Application to the Maize 50k Array. Front. Plant Sci., (11) 568699
  • Haug B., Messmer MM., Enjalbert J., Goldringer I., Forst E., Flutre T., Mary-Huard T. , Hohmann P.. (2021) Advances in Breeding for Mixed Cropping – Incomplete Factorials and the Producer/Associate Concept. Front. Plant Sci., (11) 620400
  • Arca M., Gouesnard B., Mary-Huard T. , Le Paslier MC., Bauland C., Combes V., Madur D., Charcosset A., Nicolas SD.. (2020) Genome-wide SNP genotyping of DNA pools identifies untapped landraces and genomic regions that could enrich the maize breeding pool. ,
  • Rio S., Moreau L., Charcosset A., Mary-Huard T. . (2020) Accounting for Group-Specific Allele Effects and Admixture in Genomic Predictions: Theory and Experimental Evaluation in Maize. Genetics, 1 (216) 27-41
  • Rio S., Mary-Huard T. , Moreau L., Bauland C., Palaffre C., Madur D., Combes V., Charcosset A., Springer NM.. (2020) Disentangling group specific QTL allele effects from genetic background epistasis using admixed individuals in GWAS: An application to maize flowering. PLoS Genet, 3 (16) e1008241
  • Boussardon C., Martin-Magniette ML., Godin B., Benamar A., Vittrant B., Citerne S., Mary-Huard T. , Macherel D., Rajjou L., Budar F.. (2019) Novel Cytonuclear Combinations Modify Arabidopsis thaliana Seed Physiology and Vigor. Front Plant Sci, (10) 32
  • Forst E., Enjalbert J., Allard V., Ambroise C., Krissaane I., Mary-Huard T. , Robin S., Goldringer I.. (2019) A generalized statistical framework to assess mixing ability from incomplete mixing designs using binary or higher order variety mixtures and application to wheat. Field Crops Research, (242) 107571
  • Rio S., 2019-04-26 26/04/19, Contributions to genomic selection and association mapping in structured and admixed populations : application to maize
  • Rio S., Mary-Huard T. , Moreau L., Charcosset A.. (2019) Genomic selection efficiency and a priori estimation of accuracy in a structured dent maize panel. Theor Appl Genet, 1 (132) 81-96
  • Celisse A., Mary-Huard T. . (2018) Theoretical Analysis of Cross-Validation for Estimating the Risk of the $k$-Nearest Neighbor Classifier. Journal of Machine Learning Research, 58 (19) 1-54
  • Darracq A., Vitte C., Nicolas S., Duarte J., Pichon JP., Mary-Huard T. , Chevalier C., Bérard A., Le Paslier MC., Rogowsky P., Charcosset A., Joets J.. (2018) Sequence analysis of European maize inbred line F2 provides new insights into molecular and chromosomal characteristics of presence/absence variants. BMC Genomics, 1 (19) 119
  • Laporte F., 2018-03-13 13/03/18, Développement de méthodes statistiques pour l’identification de gènes d’intérêt en présence d’apparentement et de dominance, application à la génétique du maïs
  • Brandenburg JT., Mary-Huard T. , Rigaill G., Hearne SJ., Corti H., Joets J., Vitte C., Charcosset A., Nicolas SD., Tenaillon MI.. (2017) Independent introductions and admixtures have contributed to adaptation of European maize and its American counterparts. PLOS Genetics, 3 (13) e1006666
  • Brault V., Delattre M., Lebarbier E., Mary‐Huard T., Lévy‐Leduc C.. (2017) Estimating the Number of Block Boundaries from Diagonal Blockwise Matrices Without Penalization. Scandinavian Journal of Statistics, 2 (44) 563-580
  • Delatola EI., Lebarbier E., Mary-Huard T. , Radvanyi F., Robin S., Wong J.. (2017) SegCorr a statistical procedure for the detection of genomic regions of correlated expression. BMC Bioinformatics, 1 (18) 333
  • Laporte F., Charcosset A., Mary‐Huard T.. (2017) Estimation of the relatedness coefficients from biallelic markers, application in plant mating designs. Biometrics, 3 (73) 885-894
  • Larièpe A., Moreau L., Laborde J., Bauland C., Mezmouk S., Décousset L., Mary-Huard T. , Fiévet JB., Gallais A., Dubreuil P., Charcosset A.. (2017) General and specific combining abilities in a maize (Zea mays L.) test-cross hybrid panel: relative importance of population structure and genetic divergence between parents. Theor. Appl. Genet., 2 (130) 403-417
  • Mary-Huard T. , 2017-06-12 06/12/17, Some contributions to statistical modeling and model selection with applications to genomics and quantitative genetics
  • Desclée de Maredsous C., Oozeer R., Barbillon P., Mary-Huard T. , Delteil C., Blachier F., Tomé D., van der Beek EM., Davila AM.. (2016) High-Protein Exposure during Gestation or Lactation or after Weaning Has a Period-Specific Signature on Rat Pup Weight, Adiposity, Food Intake, and Glucose Homeostasis up to 6 Weeks of Age. J. Nutr., 1 (146) 21-29
  • Roux F., Mary-Huard T. , Barillot E., Wenes E., Botran L., Durand S., Villoutreix R., Martin-Magniette ML., Camilleri C., Budar F.. (2016) Cytonuclear interactions affect adaptive traits of the annual plant Arabidopsis thaliana in the field. Proceedings of the National Academy of Sciences of the United States of America, 13 (113) 3687-92
  • Bel L., Daudin JJ., Etienne M., Lebarbier E., Mary-Huard T. , Robin S., Vuillet C., Daudin JJ.. (2015) Modèle mixte, modélisation de la variance. , 162-189
  • Bel L., Daudin JJ., Etienne M., Lebarbier E., Mary-Huard T. , Robin S., Vuillet C., Daudin JJ.. (2015) Plans d’expérience. , 218-246
  • Desclée de Maredsous C., Oosting A., Delteil C., Blachier F., Barbillon P., Mary-Huard T. , Tome D., Oozeer R., Davila AM.. (2015) High-Protein Diet during Gestation Promotes Adiposity and Food Intake in Female Rat Pups in the Longer Term. Faseb J., 1 (29)
  • Zaag R., Tamby JP., Guichard C., Tariq Z., Rigaill G., Delannoy E., Renou JP., Balzergue S., Mary-Huard T. , Aubourg S., Martin-Magniette ML., Brunaud V.. (2015) GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response. Nucleic Acids Res, D1 (43) D1010-D1017
  • Rincent R., Moreau L., Monod H., Kuhn E., Melchinger AE., Malvar RA., Moreno-Gonzalez J., Nicolas S., Madur D., Combes V., Dumas F., Altmann T., Brunel D., Ouzunova M., Flament P., Dubreuil P., Charcosset A., Mary-Huard T. . (2014) Recovering power in association mapping panels with variable levels of linkage disequilibrium. Genetics, 1 (197) 375-87