ArticleBriefings in bioinformatics2021
DECO: a framework for jointly analyzing de novo and rare case/control variants, and biological pathways.
Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Joint analysis ofNAR genomics and bioinformatics · 2025Article
- STIGMA: Single-cell tissue-specific gene prioritization using machine learning.American journal of human genetics · 2024Article
- VBASS enables integration of single cell gene expression data in Bayesian association analysis of rare variants.Communications biology · 2023Article
- Network assisted analysis of de novo variants using protein-protein interaction information identified 46 candidate genes for congenital heart disease.PLoS genetics · 2022Article
- M-DATA: A statistical approach to jointly analyzing de novo mutations for multiple traits.PLoS genetics · 2021Article
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8 authors.
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Abstract
motivationRare variant-based analyses are beginning to identify risk genes for neuropsychiatric disorders and other diseases. However, the identified genes only account for a fraction of predicted causal genes. Recent studies have shown that rare damaging variants are significantly enriched in specific gene-sets. Methods which are able to jointly model rare variants and gene-sets to identify enriched gene-sets and use these enriched gene-sets to prioritize additional risk genes could improve understanding of the genetic architecture of diseases.
resultsWe propose DECO (Integrated analysis of de novo mutations, rare case/control variants and omics information via gene-sets), an integrated method for rare-variant and gene-set analysis. The method can (i) test the enrichment of gene-sets directly within the statistical model, and (ii) use enriched gene-sets to rank existing genes and prioritize additional risk genes for tested disorders. In simulations, DECO performs better than a homologous method that uses only variant data. To demonstrate the application of the proposed protocol, we have applied this approach to rare-variant datasets of schizophrenia. Compared with a method which only uses variant information, DECO is able to prioritize additional risk genes. AVAILABILITY: DECO can be used to analyze rare-variants and biological pathways or cell types for any disease. The package is available on Github https://github.com/hoangtn/DECO.
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