ArticleAmerican journal of human genetics2017
Practical Approaches for Whole-Genome Sequence Analysis of Heart- and Blood-Related Traits.
Article in American journal of human genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 3 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
39 citing papers in PubMed, 3 syntheses or guidelines pooled it, 57 citations in OpenAlex.
- Assessment of the functionality and usability of open-source rare variant analysis pipelines.Briefings in bioinformatics · 2025Pooled it
- Powerful, scalable and resource-efficient meta-analysis of rare variant associations in large whole genome sequencing studies.Nature genetics · 2023Pooled it
- Genome-wide analysis of common and rare variants via multiple knockoffs at biobank scale, with an application to Alzheimer disease genetics.American journal of human genetics · 2021Pooled it
- Atlas of glomerular disease-specific genetic effects on blood transcriptome.medRxiv : the preprint server for health sciences · 2026Article
- Comparative analysis of genotype imputation strategies for SNPs calling from RNA-seq.BMC genomics · 2025Article
- RetroFun-RVS: A Retrospective Family-Based Framework for Rare Variant Analysis Incorporating Functional Annotations.Genetic epidemiology · 2025Article
- A statistical framework for multi-trait rare variant analysis in large-scale whole-genome sequencing studies.Nature computational science · 2025Article
- Biostatistical Aspects of Whole Genome Sequencing Studies: Preprocessing and Quality Control.Biometrical journal. Biometrische Zeitschrift · 2024Article
- Ensemble methods for testing a global null.Journal of the Royal Statistical Society. Series B, Statistical methodology · 2024Article
- A statistical framework for powerful multi-trait rare variant analysis in large-scale whole-genome sequencing studies.bioRxiv : the preprint server for biology · 2023Article
- FAVOR: functional annotation of variants online resource and annotator for variation across the human genome.Nucleic acids research · 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
- eSCAN: scan regulatory regions for aggregate association testing using whole-genome sequencing data.Briefings in bioinformatics · 2022Article
- Simultaneous detection of novel genes and SNPs by adaptiveFrontiers in genetics · 2022Article
- A Minimax Optimal Ridge-Type Set Test for Global Hypothesis with Applications in Whole Genome Sequencing Association Studies.Journal of the American Statistical Association · 2022Article
- Simultaneous Detection of Signal Regions Using Quadratic Scan Statistics With Applications to Whole Genome Association Studies.Journal of the American Statistical Association · 2022Article
- Advances and challenges in quantitative delineation of the genetic architecture of complex traits.Quantitative biology (Beijing, China) · 2021Article
- Identification of putative causal loci in whole-genome sequencing data via knockoff statistics.Nature communications · 2021Article
- Rare variant association testing in the non-coding genome.Human genetics · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 4 institutions in 1 country.
Funding
Abstract
Whole-genome sequencing (WGS) allows for a comprehensive view of the sequence of the human genome. We present and apply integrated methodologic steps for interrogating WGS data to characterize the genetic architecture of 10 heart- and blood-related traits in a sample of 1,860 African Americans. In order to evaluate the contribution of regulatory and non-protein coding regions of the genome, we conducted aggregate tests of rare variation across the entire genomic landscape using a sliding window, complemented by an annotation-based assessment of the genome using predefined regulatory elements and within the first intron of all genes. These tests were performed treating all variants equally as well as with individual variants weighted by a measure of predicted functional consequence. Significant findings were assessed in 1,705 individuals of European ancestry. After these steps, we identified and replicated components of the genomic landscape significantly associated with heart- and blood-related traits. For two traits, lipoprotein(a) levels and neutrophil count, aggregate tests of low-frequency and rare variation were significantly associated across multiple motifs. For a third trait, cardiac troponin T, investigation of regulatory domains identified a locus on chromosome 9. These practical approaches for WGS analysis led to the identification of informative genomic regions and also showed that defined non-coding regions, such as first introns of genes and regulatory domains, are associated with important risk factor phenotypes. This study illustrates the tractable nature of WGS data and outlines an approach for characterizing the genetic architecture of complex traits.
Indexed as
Identifiers
What OpenQuestion holds
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.