Author

Simon Rio

Centre de Coopération Internationale en Recherche Agronomique pour le DéveloppementORCID 0000-0001-7014-8789Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetics· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:benchmarking· 2 Research Focus:gene regulatory network inference· 2 Organism:plant (other)· 2 Approach:experimental assay· 1 Research Focus:genome assembly· 1 Research Focus:GWAS / association mapping· 1 Assay:GWAS summary statistics· 1

Frequent Co-Authors

Alain CharcossetiD· 2 shared Laurence MoreauiD· 2 shared Tristan Mary‐HuardiD· 2 shared Angélique D’HontiD· 1 shared Carine PalaffreiD· 1 shared Cyril BaulandiD· 1 shared Delphine MaduriD· 1 shared Olivier GarsmeuriD· 1 shared

Activity by Year

2020-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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2 shared papersGenetics

Alain CharcossetORCID

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3 papers

Recent·Most cited

BioinformaticsPeer Community JournalPeer-reviewedSep 25, 2025

HaploCharmer: a Snakemake workflow for read-scale haplotype calling adapted to polyploids

Simon Rio, Sophie Abdallah, Théo Durand…·Olivier Garsmeur

HaploCharmer is a Snakemake workflow for read-scale haplotype calling in polyploids, validated on sugarcane and Saccharum data, identifying high-quality haplotypes with low false positives.

1 citation

plant (other)whole-genome sequencing

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GeneticsbioRxivPreprintDec 18, 2022

Detecting directional and non-directional epistasis in bi-parental populations using genomic data

Simon Rio, Alain Charcosset, Laurence Moreau, Tristan Mary‐Huard

The paper introduces a method to detect directional and non-directional epistasis in bi-parental populations using genomic data and applies it to maize and soybean populations, finding significant epistatic effects.

DOI 10.1101/2022.12.18.520958

statistical modelgene regulatory network inference

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GeneticsPLoS GeneticsPeer-reviewedMar 4, 2020

Disentangling group specific QTL allele effects from genetic background epistasis using admixed individuals in GWAS: an application to maize flowering

Simon Rio, Tristan Mary‐Huard, Laurence Moreau…·Alain Charcosset

The paper introduces a GWAS method to identify QTLs with group-specific allele effects in admixed populations, applied to maize flowering time data.

28 citations

plant (other)GWAS summary statistics

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