AIMC Topic: Quantitative Trait Loci

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TVAR: assessing tissue-specific functional effects of non-coding variants with deep learning.

Bioinformatics (Oxford, England) Oct 14, 2022
MOTIVATION: Analysis of whole-genome sequencing (WGS) for genetics is still a challenge due to the lack of accurate functional annotation of non-coding variants, especially the rare ones. As eQTLs have been extensively implicated in the genetics of h...
Humans Diabetes Mellitus, Type 2 Polymorphism, Single Nucleotide Quantitative Trait Loci Software Deep Learning Genome-Wide Association Study
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Deep learning model reveals potential risk genes for ADHD, especially Ephrin receptor gene EPHA5.

Briefings in bioinformatics Nov 5, 2021
Attention deficit hyperactivity disorder (ADHD) is a common neurodevelopmental disorder. Although genome-wide association studies (GWAS) identify the risk ADHD-associated variants and genes with significant P-values, they may neglect the combined eff...
Attention Deficit Disorder with Hyperactivity Receptor, EphA5 Gene Ontology Quantitative Trait Loci Genome-Wide Association Study Linkage Disequilibrium Humans ROC Curve Biomarkers Polymorphism, Single Nucleotide Genetic Predisposition to Disease Deep Learning Computational Biology Area Under Curve
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Deep learning-based high-throughput phenotyping accelerates gene discovery for stomatal traits.

Plant physiology Nov 3, 2021
Quantitative Trait Loci Droughts Plant Stomata Zea mays Sorghum Neural Networks, Computer Algorithms Phenotype Deep Learning Genome-Wide Association Study Water
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Optical topometry and machine learning to rapidly phenotype stomatal patterning traits for maize QTL mapping.

Plant physiology Nov 3, 2021
Stomata are adjustable pores on leaf surfaces that regulate the tradeoff of CO2 uptake with water vapor loss, thus having critical roles in controlling photosynthetic carbon gain and plant water use. The lack of easy, rapid methods for phenotyping ep...
Quantitative Trait Loci Genes, Plant Chromosome Mapping Machine Learning Phenotype Zea mays Botany Plant Stomata
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Combining artificial intelligence: deep learning with Hi-C data to predict the functional effects of non-coding variants.

Bioinformatics (Oxford, England) Jun 16, 2021
MOTIVATION: Although genome-wide association studies (GWASs) have identified thousands of variants for various traits, the causal variants and the mechanisms underlying the significant loci are largely unknown. In this study, we aim to predict non-co...
Genome-Wide Association Study Polymorphism, Single Nucleotide Quantitative Trait Loci Artificial Intelligence Deep Learning
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Statistical and Machine Learning Methods for eQTL Analysis.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2020
An immense amount of observable diversity exists for all traits and across global populations. In the post-genomic era, equipped with efficient sequencing capabilities and better genotyping methods, we are now able to more fully appreciate how regula...
Genome-Wide Association Study Computational Biology Data Interpretation, Statistical Gene Expression Humans Quantitative Trait Loci Machine Learning Chromosome Mapping
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Convolutional neural network model to predict causal risk factors that share complex regulatory features.

Nucleic acids research Dec 16, 2019
Major progress in disease genetics has been made through genome-wide association studies (GWASs). One of the key tasks for post-GWAS analyses is to identify causal noncoding variants with regulatory function. Here, on the basis of >2000 functional fe...
Humans Neural Networks, Computer Mental Disorders Risk Factors Genome-Wide Association Study Genetic Predisposition to Disease Regulatory Sequences, Nucleic Acid Polymorphism, Single Nucleotide Autoimmune Diseases Quantitative Trait Loci
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TAGOOS: genome-wide supervised learning of non-coding loci associated to complex phenotypes.

Nucleic acids research Aug 22, 2019
Genome-wide association studies (GWAS) associate single nucleotide polymorphisms (SNPs) to complex phenotypes. Most human SNPs fall in non-coding regions and are likely regulatory SNPs, but linkage disequilibrium (LD) blocks make it difficult to dist...
Quantitative Trait Loci Linkage Disequilibrium Humans Regulatory Sequences, Nucleic Acid Polymorphism, Single Nucleotide Supervised Machine Learning Computational Biology Gene Expression Regulation Internet Phenotype Genome-Wide Association Study Genetic Predisposition to Disease
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Building a livestock genetic and genomic information knowledgebase through integrative developments of Animal QTLdb and CorrDB.

Nucleic acids research Jan 8, 2019
Successful development of biological databases requires accommodation of the burgeoning amounts of data from high-throughput genomics pipelines. As the volume of curated data in Animal QTLdb (https://www.animalgenome.org/QTLdb) increases exponentiall...
Knowledge Bases Quantitative Trait Loci Genome-Wide Association Study Databases, Genetic Animals Poultry Livestock
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Computational aspects underlying genome to phenome analysis in plants.

The Plant journal : for cell and molecular biology Jan 1, 2019
Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high-throughput plant phenotyping is becoming widely adopted in the plant community, promisi...
Genome, Plant Quantitative Trait Loci Phenomics Genomics Genetic Association Studies Machine Learning Plants Phenotype
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