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...
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| Veröffentlicht in: | PloS one 2015-04, Vol.10 (4), p.e0124579-e0124579 |
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| creator | Giollo, Manuel Minervini, Giovanni Scalzotto, Marta Leonardi, Emanuela Ferrari, Carlo Tosatto, Silvio C E |
| 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/. |
| doi_str_mv | 10.1371/journal.pone.0124579 |
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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/.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0124579</identifier><identifier>PMID: 25893845</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>ABO Blood-Group System - genetics ; ABO system ; Annotations ; Blood ; Blood Group Antigens - genetics ; Blood groups ; Blood tests ; Downloading ; Exons - genetics ; Genome, Human ; Genomes ; Genomics ; Haplotypes ; Haplotypes - genetics ; High-Throughput Nucleotide Sequencing - methods ; Humans ; Minority & ethnic groups ; Molecular Sequence Annotation ; Mutation - genetics ; Next-generation sequencing ; Phenotype ; Polymorphism, Single Nucleotide - genetics ; Precision medicine ; Predictions ; Protocol (computers) ; Software</subject><ispartof>PloS one, 2015-04, Vol.10 (4), p.e0124579-e0124579</ispartof><rights>COPYRIGHT 2015 Public Library of Science</rights><rights>2015 Giollo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2015 Giollo et al 2015 Giollo et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c758t-d97db252fed7f99f99049a1081392eecabbcadfd3a9533f61514f723350e96d43</citedby><cites>FETCH-LOGICAL-c758t-d97db252fed7f99f99049a1081392eecabbcadfd3a9533f61514f723350e96d43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4404330/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4404330/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,315,728,781,785,865,886,2103,2929,23868,27926,27927,53793,53795</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25893845$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Seo, Jeong-Sun</contributor><creatorcontrib>Giollo, Manuel</creatorcontrib><creatorcontrib>Minervini, Giovanni</creatorcontrib><creatorcontrib>Scalzotto, Marta</creatorcontrib><creatorcontrib>Leonardi, Emanuela</creatorcontrib><creatorcontrib>Ferrari, Carlo</creatorcontrib><creatorcontrib>Tosatto, Silvio C E</creatorcontrib><title>BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data</title><title>PloS one</title><addtitle>PLoS One</addtitle><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. 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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. 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| subjects | ABO Blood-Group System - genetics ABO system Annotations Blood Blood Group Antigens - genetics Blood groups Blood tests Downloading Exons - genetics Genome, Human Genomes Genomics Haplotypes Haplotypes - genetics High-Throughput Nucleotide Sequencing - methods Humans Minority & ethnic groups Molecular Sequence Annotation Mutation - genetics Next-generation sequencing Phenotype Polymorphism, Single Nucleotide - genetics Precision medicine Predictions Protocol (computers) Software |
| title | BOOGIE: Predicting Blood Groups from High Throughput Sequencing Data |
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