Navigating the pitfalls of applying machine learning in genomics
The scale of genetic, epigenomic, transcriptomic, cheminformatic and proteomic data
available today, coupled with easy-to-use machine learning (ML) toolkits, has propelled the …
available today, coupled with easy-to-use machine learning (ML) toolkits, has propelled the …
A spectrum of explainable and interpretable machine learning approaches for genomic studies
The advancement of high‐throughput genomic assays has led to enormous growth in the
availability of large‐scale biological datasets. Over the last two decades, these increasingly …
availability of large‐scale biological datasets. Over the last two decades, these increasingly …
Tree-based QTL mapping with expected local genetic relatedness matrices
Understanding the genetic basis of complex phenotypes is a central pursuit of genetics.
Genome-wide association studies (GWASs) are a powerful way to find genetic loci …
Genome-wide association studies (GWASs) are a powerful way to find genetic loci …
Gene regulatory effects of a large chromosomal inversion in highland maize
T Crow, J Ta, S Nojoomi, MR Aguilar-Rangel… - PLoS …, 2020 - journals.plos.org
Chromosomal inversions play an important role in local adaptation. Inversions can capture
multiple locally adaptive functional variants in a linked block by repressing recombination …
multiple locally adaptive functional variants in a linked block by repressing recombination …
Genome wide association mapping for agronomic, fruit quality, and root architectural traits in tomato under organic farming conditions
P Tripodi, S Soler, G Campanelli, MJ Díez, S Esposito… - BMC Plant …, 2021 - Springer
Background Opportunity and challenges of the agriculture scenario of the next decades will
face increasing demand for secure food through approaches able to minimize the input to …
face increasing demand for secure food through approaches able to minimize the input to …
MegaLMM: mega-scale linear mixed models for genomic predictions with thousands of traits
Large-scale phenotype data can enhance the power of genomic prediction in plant and
animal breeding, as well as human genetics. However, the statistical foundation of multi-trait …
animal breeding, as well as human genetics. However, the statistical foundation of multi-trait …
An adaptive teosinte mexicana introgression modulates phosphatidylcholine levels and is associated with maize flowering time
AC Barnes, F Rodríguez-Zapata… - Proceedings of the …, 2022 - National Acad Sciences
Native Americans domesticated maize (Zea mays ssp. mays) from lowland teosinte
parviglumis (Zea mays ssp. parviglumis) in the warm Mexican southwest and brought it to …
parviglumis (Zea mays ssp. parviglumis) in the warm Mexican southwest and brought it to …
Efficient variance components analysis across millions of genomes
While variance components analysis has emerged as a powerful tool in complex trait
genetics, existing methods for fitting variance components do not scale well to large-scale …
genetics, existing methods for fitting variance components do not scale well to large-scale …
Efficient ReML inference in variance component mixed models using a Min-Max algorithm
F Laporte, A Charcosset… - PLoS computational …, 2022 - journals.plos.org
Since their introduction in the 50's, variance component mixed models have been widely
used in many application fields. In this context, ReML estimation is by far the most popular …
used in many application fields. In this context, ReML estimation is by far the most popular …
Matrix sketching framework for linear mixed models in association studies
Linear mixed models (LMMs) have been widely used in genome-wide association studies to
control for population stratification and cryptic relatedness. However, estimating LMM …
control for population stratification and cryptic relatedness. However, estimating LMM …