Mathias Lorieux

NOISYmputer improves genotype and recombination breakpoint imputation from noisy low-coverage sequencing data, outperforming existing tools in accuracy and efficiency.

The paper constructs a pan-genome inversion index for Asian rice using 16 genomes and finds a high inversion rate with functional implications.

The paper identifies four new QTLs for rice hoja blanca resistance in indica varieties and confirms the wide-range action of an existing QTL, providing insights for marker-aided breeding.

The paper introduces a fast unbiased maximum-likelihood estimator for recombination frequency in F2 crosses, showing it is more efficient than an EM algorithm equivalent and better than a previous estimate.

The paper generates 12 new high-quality rice reference genomes to expand the genetic diversity coverage of cultivated rice, forming a comprehensive pan-genome resource with 16 reference sequences.

The paper analyzes genetic diversity in Japonica rice using the 3K RG dataset, identifying multiple introgression streams from different geographic regions and subgroups.

NOISYmputer improves genotype imputation for noisy low-coverage sequencing data in bi-parental populations by addressing missing data, errors, and heterozygous loci.

The paper proposes a method to identify spurious QTLs by comparing expected test statistic values at putative QTL positions with observed values.

MapDisto 2.0 constructs genetic linkage maps with features for handling large datasets, VCF import, linkage detection, data imputation, and QTL analysis.