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Genome-Wide Association Study

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DeepPerVar: a multi-modal deep learning framework for functional interpretation of genetic variants in personal genome.

Bioinformatics (Oxford, England)
MOTIVATION: Understanding the functional consequence of genetic variants, especially the non-coding ones, is important but particularly challenging. Genome-wide association studies (GWAS) or quantitative trait locus analyses may be subject to limited...

Interpretable deep learning translation of GWAS and multi-omics findings to identify pathobiology and drug repurposing in Alzheimer's disease.

Cell reports
Translating human genetic findings (genome-wide association studies [GWAS]) to pathobiology and therapeutic discovery remains a major challenge for Alzheimer's disease (AD). We present a network topology-based deep learning framework to identify dise...

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

Bioinformatics (Oxford, England)
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...

DeepLUCIA: predicting tissue-specific chromatin loops using Deep Learning-based Universal Chromatin Interaction Annotator.

Bioinformatics (Oxford, England)
MOTIVATION: The importance of chromatin loops in gene regulation is broadly accepted. There are mainly two approaches to predict chromatin loops: transcription factor (TF) binding-dependent approach and genomic variation-based approach. However, neit...

transferGWAS: GWAS of images using deep transfer learning.

Bioinformatics (Oxford, England)
MOTIVATION: Medical images can provide rich information about diseases and their biology. However, investigating their association with genetic variation requires non-standard methods. We propose transferGWAS, a novel approach to perform genome-wide ...

The COPILOT Raw Illumina Genotyping QC Protocol.

Current protocols
The Illumina genotyping microarrays generate data in image format, which is processed by the platform-specific software GenomeStudio, followed by an array of complex bioinformatics analyses that rely on various software, different programming languag...

Deep learning-based identification of genetic variants: application to Alzheimer's disease classification.

Briefings in bioinformatics
Deep learning is a promising tool that uses nonlinear transformations to extract features from high-dimensional data. Deep learning is challenging in genome-wide association studies (GWAS) with high-dimensional genomic data. Here we propose a novel t...

Genome-wide association study-based prediction of atrial fibrillation using artificial intelligence.

Open heart
OBJECTIVE: We previously reported early-onset atrial fibrillation (AF) associated genetic loci among a Korean population. We explored whether the AF-associated single-nucleotide polymorphisms (SNPs) selected from the Genome-Wide Association Study (GW...

RefRGim: an intelligent reference panel reconstruction method for genotype imputation with convolutional neural networks.

Briefings in bioinformatics
Genotype imputation is a statistical method for estimating missing genotypes from a denser haplotype reference panel. Existing methods usually performed well on common variants, but they may not be ideal for low-frequency and rare variants. Previous ...

Deep learning model reveals potential risk genes for ADHD, especially Ephrin receptor gene EPHA5.

Briefings in bioinformatics
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...