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BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data
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. AB...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4404330/ https://www.ncbi.nlm.nih.gov/pubmed/25893845 http://dx.doi.org/10.1371/journal.pone.0124579 |
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author | Giollo, Manuel Minervini, Giovanni Scalzotto, Marta Leonardi, Emanuela Ferrari, Carlo Tosatto, Silvio C. E. |
author_facet | Giollo, Manuel Minervini, Giovanni Scalzotto, Marta Leonardi, Emanuela Ferrari, Carlo Tosatto, Silvio C. E. |
author_sort | Giollo, Manuel |
collection | PubMed |
description | 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/. |
format | Online Article Text |
id | pubmed-4404330 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-44043302015-05-02 BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data Giollo, Manuel Minervini, Giovanni Scalzotto, Marta Leonardi, Emanuela Ferrari, Carlo Tosatto, Silvio C. E. PLoS One Research Article 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/. Public Library of Science 2015-04-20 /pmc/articles/PMC4404330/ /pubmed/25893845 http://dx.doi.org/10.1371/journal.pone.0124579 Text en © 2015 Giollo et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Giollo, Manuel Minervini, Giovanni Scalzotto, Marta Leonardi, Emanuela Ferrari, Carlo Tosatto, Silvio C. E. BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data |
title | BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data |
title_full | BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data |
title_fullStr | BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data |
title_full_unstemmed | BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data |
title_short | BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data |
title_sort | boogie: predicting blood groups from high throughput sequencing data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4404330/ https://www.ncbi.nlm.nih.gov/pubmed/25893845 http://dx.doi.org/10.1371/journal.pone.0124579 |
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