Author

Basile Jumentier

Institut polytechnique de Grenoble

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 3 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Assay:DNA methylation· 3 Approach:statistical model· 3 Research Focus:GWAS / association mapping· 2 Organism:human· 2 Assay:whole-genome sequencing· 2 Organism:Arabidopsis· 1 Approach:benchmark study· 1 Research Focus:benchmarking· 1

Frequent Co-Authors

Olivier FrançoisiD· 3 shared Barbara HeudeiD· 2 shared Johanna LepeuleiD· 2 shared Kévin Caye· 2 shared A ArnaudiD· 1 shared Aliaksandra KakoichankavaiD· 1 shared Anne-Françoise BattoiD· 1 shared Aurélia Baurès· 1 shared

Activity by Year

2018-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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3 shared papersBioinformatics

Olivier FrançoisORCID

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Author profile →

4 papers

Recent·Most cited

High Dimensional Mediation Analysis: a new method applied to maternal smoking, placental DNA methylation and birth outcomes

Basile Jumentier, Claire-Cécile Barrot, Maxime Estavoyer, Jörg Tost, Barbara Heude, Olivier François, Johanna Lepeule

The paper develops HDMAX2, a method for high-dimensional mediation analysis, and applies it to study the indirect effects of maternal smoking on birth outcomes via placental DNA methylation.

Environmental Health Perspectives · Apr 1, 2023Peer-reviewedGenetic & Genomic Medicine

Sparse latent factor regression models for genome-wide and epigenome-wide association studies

Basile Jumentier, Kévin Caye, Barbara Heude, Johanna Lepeule, Olivier François

This paper introduces sparse latent factor regression models for genome-wide and epigenome-wide association studies, showing improved statistical performance and robustness in both simulated and real data applications.

Statistical Applications in Genetics and Molecular Biology · Jan 1, 2022Peer-reviewedBioinformatics

DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification

Clémentine Decamps, A Arnaud, Florent Petitprez, Mira Ayadi, Aurélia Baurès, Lucile Armenoult, Nicolas Alcala, Francisco Avila Cobos, Luciana Batista, Anne-Françoise Batto, Yuna Blum, Florent Chuffart, Jerome F. Cros, L. Dirian, Daria Doncevic, , Magali Richard

DECONbench benchmarks deconvolution methods for quantifying tumor cell-type heterogeneity by providing datasets, tools, and performance evaluation.

BMC Bioinformatics · Oct 2, 2021Peer-reviewedBioinformatics

LFMM 2.0: Latent factor models for confounder adjustment in genome and epigenome-wide association studies

Kévin Caye, Basile Jumentier, Olivier François

LFMM 2.0 improves confounder adjustment in genome and epigenome-wide association studies using latent factor models, outperforming existing methods in simulations and providing new insights into disease mechanisms.

bioRxiv · May 14, 2018 · PreprintBioinformatics