Everything about Transcriptome-wide association study
Transcriptome-wide association study (TWAS) is a genetic methodology that can be used to compare the genetic components of gene expression and the genetic components of a trait to determine if an association is present between the two components. TWAS are useful for the identification and prioritization of candidate causal genes in candidate gene analysis following genome-wide association studies. TWAS looks at the RNA products of a specific tissue and gives researchers the abilities to look at the genes being expressed as well as gene expression levels, which varies by tissue type. TWAS are valuable and flexible bioinformatics tools that looks at the associations between the expressions of genes and complex traits and diseases. By looking at the association between gene expression and the trait expressed, genetic regulatory mechanisms can be investigated for the role that they play in the development of specific traits and diseases. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Transcriptome-wide association studyA 5-minute orientation
- Skim a recent paper: Nasal airway transcriptome-wide association study of asthma reveals genetically driven mucus pathobiologyInfluential work since 2022
- Pick up a classic book: Principles of gene manipulation and genomicsThe most-reprinted book on the subject
- Read the landmark paper: Large-scale transcriptome-wide association study identifies new prostate cancer risk regionsCited 154 times
- Go sideways: Expression quantitative trait lociA closely related topic
- Go sideways: Fine-mappingA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Large-scale transcriptome-wide association study identifies new prostate cancer risk regions
Power analysis of transcriptome-wide association study: Implications for practical protocol choice
Transcriptome‐wide association study reveals candidate causal genes for lung cancer
A transcriptome-wide association study identifies susceptibility genes for Parkinson’s disease
Transcriptome-wide association study identifies new susceptibility genes and pathways for depression
Conditional transcriptome-wide association study for fine-mapping candidate causal genes
Transcriptome-wide association study of coronary artery disease identifies novel susceptibility genes
Transcriptome-wide association study identifies susceptibility genes for rheumatoid arthritis
🆕 Influential since 2022
Nasal airway transcriptome-wide association study of asthma reveals genetically driven mucus pathobiology
Alternative polyadenylation transcriptome-wide association study identifies APA-linked susceptibility genes in brain disorders
A cross-tissue transcriptome-wide association study reveals novel susceptibility genes for migraine
A Single-Nucleus Transcriptome-Wide Association Study Implicates Novel Genes in Depression Pathogenesis
Association of Early Childhood Caries with Bitter Taste Receptors: A Meta-Analysis of Genome-Wide Association Studies and Transcriptome-Wide Association Study
📚 Books worth reading
Principles of gene manipulation and genomicsS. B. Primrose · 2006
Ovarian cancerAnastasia Malek, Oleg Tchernitsa · 2013- 📕Genetics in diabetesAnna L. Gloyn, Mark I. McCarthy · 2014
Guide to yeast geneticsJonathan Weissman, Christine Guthrie · 2010
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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- Fine-mapping Fine-mapping is a set of methods in genetics used to identify the genetic variant or variants, often single-nucleotide polymorphisms (SNPs), most likely…
- Complex traits Complex traits, also known as polygenic or multigenic traits, are phenotypes determined by the interaction of multiple genetic and environmental factors…
- Genome-wide association study In genomics, a genome-wide association study (GWA study, or GWAS), is an observational study of a genome-wide set of genetic variants in different individuals…
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- Eric R. Gamazon Eric R. Gamazon is a statistical geneticist in Vanderbilt University, with faculty affiliations in the Division of Genetic Medicine, Data Science Institute…
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