ReviewHuman genetics2020
Rare variant association testing in the non-coding genome.
Review in Human genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
- Assessment of the functionality and usability of open-source rare variant analysis pipelines.Briefings in bioinformatics · 2025Pooled it
- Refining the diagnosis of 46,XY disorders of sex development: insight from whole-exome sequencing.Orphanet journal of rare diseases · 2026Article
- COBT: a gene-based rare variant burden test for case-only study designs using aggregated genotypes from public reference cohorts.Genome medicine · 2026Article
- Noncoding rare variant associations with blood traits in 166,740 UK Biobank genomes.Nature genetics · 2025Article
- A method to estimate the contribution of rare coding variants to complex trait heritability.Nature communications · 2024Article
- Rare variants in long non-coding RNAs are associated with blood lipid levels in the TOPMed whole-genome sequencing study.American journal of human genetics · 2023Article
- Unravelling the genetic architecture of human complex traits through whole genome sequencing.Nature communications · 2023Article
- Multimodal single cell analysis infers widespread enhancer co-activity in a lymphoblastoid cell line.Communications biology · 2023Article
- A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies.Nature methods · 2022Article
- Testing for association with rare variants in the coding and non-coding genome: RAVA-FIRST, a new approach based on CADD deleteriousness score.PLoS genetics · 2022Article
- Optimized splitting of mixed-species RNA sequencing data.Journal of bioinformatics and computational biology · 2022Article
- A haplotype in the dipeptidyl peptidase 4 gene impacts glycemic-related traits of Brazilian older adults.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2022Article
- Mining massive genomic data of two Swiss Braunvieh cattle populations reveals six novel candidate variants that impair reproductive success.Genetics, selection, evolution : GSE · 2021Article
- Low frequency variants associated with leukocyte telomere length in the Singapore Chinese population.Communications biology · 2021Article
- Modeling transcriptional regulation using gene regulatory networks based on multi-omics data sources.BMC bioinformatics · 2021Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The development of next-generation sequencing technologies has opened-up some new possibilities to explore the contribution of genetic variants to human diseases and in particular that of rare variants. Statistical methods have been developed to test for association with rare variants that require the definition of testing units and, in these testing units, the selection of qualifying variants to include in the test. In the coding regions of the genome, testing units are usually the different genes and qualifying variants are selected based on their functional effects on the encoded proteins. Extending these tests to the non-coding regions of the genome is challenging. Testing units are difficult to define as the non-coding genome organisation is still rather unknown. Qualifying variants are difficult to select as the functional impact of non-coding variants on gene expression is hard to predict. These difficulties could explain why very few investigators so far have analysed the non-coding parts of their whole genome sequencing data. These non-coding parts yet represent the vast majority of the genome and some studies suggest that they could play a major role in disease susceptibility. In this review, we discuss recent experimental and statistical developments to gain knowledge on the non-coding genome and how this knowledge could be used to include rare non-coding variants in association tests. We describe the few studies that have considered variants from the non-coding genome in association tests and how they managed to define testing units and select qualifying variants.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.