ArticlePloS one2015
BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Utility ofAnnals of laboratory medicine · 2025Article
- A machine-learning method for biobank-scale genetic prediction of blood group antigens.PLoS computational biology · 2024Article
- Haplotype sequence collection of ABO blood group alleles by long-read sequencing reveals putative A1-diagnostic variants.Blood advances · 2023Article
- Article
- Using whole-genome sequencing to characterize clinically significant blood groups among healthy older Australians.Blood advances · 2022Article
- Article
- Cataloguing experimentally confirmed 80.7 kb-long ACKR1 haplotypes from the 1000 Genomes Project database.BMC bioinformatics · 2021Article
- A novel algorithm comprehensively characterizes human RH genes using whole-genome sequencing data.Blood advances · 2020Article
- Automated typing of red blood cell and platelet antigens: a whole-genome sequencing study.The Lancet. Haematology · 2018Article
- Prediction of Protein-Protein Interactions from Amino Acid Sequences Based on Continuous and Discrete Wavelet Transform Features.Molecules (Basel, Switzerland) · 2018Article
- Crohn disease risk prediction-Best practices and pitfalls with exome data.Human mutation · 2017Article
- Whole-exome sequencing forBlood advances · 2017Article
- Detailed Characterization of Human Induced Pluripotent Stem Cells Manufactured for Therapeutic Applications.Stem cell reviews and reports · 2016Article
- ABO allele-level frequency estimation based on population-scale genotyping by next generation sequencing.BMC genomics · 2016Article
- Comprehensive red blood cell and platelet antigen prediction from whole genome sequencing: proof of principle.Transfusion · 2016Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Over the last decade, we have witnessed an incredible growth in the amount of available genotype data due to high throughput sequencing (HTS) techniques. This information may be used to predict phenotypes of medical relevance, and pave the way towards personalized medicine. Blood phenotypes (e.g. ABO and Rh) are a purely genetic trait that has been extensively studied for decades, with currently over thirty known blood groups. Given the public availability of blood group data, it is of interest to predict these phenotypes from HTS data which may translate into more accurate blood typing in clinical practice. Here we propose BOOGIE, a fast predictor for the inference of blood groups from single nucleotide variant (SNV) databases. We focus on the prediction of thirty blood groups ranging from the well known ABO and Rh, to the less studied Junior or Diego. BOOGIE correctly predicted the blood group with 94% accuracy for the Personal Genome Project whole genome profiles where good quality SNV annotation was available. Additionally, our tool produces a high quality haplotype phase, which is of interest in the context of ethnicity-specific polymorphisms or traits. The versatility and simplicity of the analysis make it easily interpretable and allow easy extension of the protocol towards other phenotypes. BOOGIE can be downloaded from URL http://protein.bio.unipd.it/download/.
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