AIMC Topic: Quantitative Trait Loci
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QTG-Finder: A Machine-Learning Based Algorithm To Prioritize Causal Genes of Quantitative Trait Loci in Arabidopsis and Rice.
G3 (Bethesda, Md.)
Oct 7, 2019
Linkage mapping is one of the most commonly used methods to identify genetic loci that determine a trait. However, the loci identified by linkage mapping may contain hundreds of candidate genes and require a time-consuming and labor-intensive fine ma...
Multivariate Cluster-Based Multifactor Dimensionality Reduction to Identify Genetic Interactions for Multiple Quantitative Phenotypes.
BioMed research international
Jul 11, 2019
To understand the pathophysiology of complex diseases, including hypertension, diabetes, and autism, deleterious phenotypes are unlikely due to the effects of single genes, but rather, gene-gene interactions (GGIs), which are widely analyzed by multi...
A directed learning strategy integrating multiple omic data improves genomic prediction.
Plant biotechnology journal
Apr 14, 2019
Genomic prediction (GP) aims to construct a statistical model for predicting phenotypes using genome-wide markers and is a promising strategy for accelerating molecular plant breeding. However, current progress of phenotype prediction using genomic d...
Identification of optimal prediction models using multi-omic data for selecting hybrid rice.
Heredity
Mar 25, 2019
Genomic prediction benefits hybrid rice breeding by increasing selection intensity and accelerating breeding cycles. With the rapid advancement of technology, other omic data, such as metabolomic data and transcriptomic data, are readily available fo...
Improving eQTL Analysis Using a Machine Learning Approach for Data Integration: A Logistic Model Tree Solution.
Journal of computational biology : a journal of computational molecular cell biology
Jul 27, 2018
Expression quantitative trait loci (eQTL) analysis is an emerging method for establishing the impact of genetic variations (such as single nucleotide polymorphisms) on the expression levels of genes. Although different methods for evaluating the impa...
Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk.
Nature genetics
Jul 16, 2018
Key challenges for human genetics, precision medicine and evolutionary biology include deciphering the regulatory code of gene expression and understanding the transcriptional effects of genome variation. However, this is extremely difficult because ...
A hidden Markov tree model for testing multiple hypotheses corresponding to Gene Ontology gene sets.
BMC bioinformatics
Mar 27, 2018
BACKGROUND: Testing predefined gene categories has become a common practice for scientists analyzing high throughput transcriptome data. A systematic way of testing gene categories leads to testing hundreds of null hypotheses that correspond to nodes...
The R-package GenomicTools for multifactor dimensionality reduction and the analysis of (exploratory) Quantitative Trait Loci.
Computer methods and programs in biomedicine
Aug 30, 2017
BACKGROUND AND OBJECTIVES: We introduce the R-package GenomicTools to perform, among others, a Multifactor Dimensionality Reduction (MDR) for the identification of SNP-SNP interactions. The package further provides a new class of tests for an (explor...
Multiple Trait Covariance Association Test Identifies Gene Ontology Categories Associated with Chill Coma Recovery Time in Drosophila melanogaster.
Scientific reports
May 25, 2017
The genomic best linear unbiased prediction (GBLUP) model has proven to be useful for prediction of complex traits as well as estimation of population genetic parameters. Improved inference and prediction accuracy of GBLUP may be achieved by identify...
Computer vision and machine learning for robust phenotyping in genome-wide studies.
Scientific reports
Mar 8, 2017
Traditional evaluation of crop biotic and abiotic stresses are time-consuming and labor-intensive limiting the ability to dissect the genetic basis of quantitative traits. A machine learning (ML)-enabled image-phenotyping pipeline for the genetic stu...
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