ArticlePacific Symposium on Biocomputing. Pacific Symposium on Biocomputing2013
Using BioBin to explore rare variant population stratification.
Article in Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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Who cites it
11 citing papers in PubMed, 14 citations in OpenAlex.
- Real world scenarios in rare variant association analysis: the impact of imbalance and sample size on the power in silico.BMC bioinformatics · 2019Article
- Rare variants in the splicing regulatory elements of EXOC3L4 are associated with brain glucose metabolism in Alzheimer's disease.BMC medical genomics · 2018Article
- Novel features and enhancements in BioBin, a tool for the biologically inspired binning and association analysis of rare variants.Bioinformatics (Oxford, England) · 2018Article
- Codon bias among synonymous rare variants is associated with Alzheimer's disease imaging biomarker.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2018Article
- Knowledge-driven binning approach for rare variant association analysis: application to neuroimaging biomarkers in Alzheimer's disease.BMC medical informatics and decision making · 2017Article
- Dissecting ancestry genomic background in substance dependence genome-wide association studies.Pharmacogenomics · 2015Article
- Individualized medicine enabled by genomics in Saudi Arabia.BMC medical genomics · 2015Review
- Genomic architecture of pharmacological efficacy and adverse events.Pharmacogenomics · 2014Review
- Adjusting for population stratification in a fine scale with principal components and sequencing data.Genetic epidemiology · 2013Article
- BioBin: a bioinformatics tool for automating the binning of rare variants using publicly available biological knowledge.BMC medical genomics · 2013Article
- Low frequency variants, collapsed based on biological knowledge, uncover complexity of population stratification in 1000 genomes project data.PLoS genetics · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
Rare variants (RVs) will likely explain additional heritability of many common complex diseases; however, the natural frequencies of rare variation across and between human populations are largely unknown. We have developed a powerful, flexible collapsing method called BioBin that utilizes prior biological knowledge using multiple publicly available database sources to direct analyses. Variants can be collapsed according to functional regions, evolutionary conserved regions, regulatory regions, genes, and/or pathways without the need for external files. We conducted an extensive comparison of rare variant burden differences (MAF < 0.03) between two ancestry groups from 1000 Genomes Project data, Yoruba (YRI) and European descent (CEU) individuals. We found that 56.86% of gene bins, 72.73% of intergenic bins, 69.45% of pathway bins, 32.36% of ORegAnno annotated bins, and 9.10% of evolutionary conserved regions (shared with primates) have statistically significant differences in RV burden. Ongoing efforts include examining additional regional characteristics using regulatory regions and protein binding domains. Our results show interesting variant differences between two ancestral populations and demonstrate that population stratification is a pervasive concern for sequence analyses.
Indexed as
Identifiers
23424138PMC3638724W2272048599What 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.