Academic Journal
Discovering Genome-Wide Tag SNPs Based on the Mutual Information of the Variants
| Τίτλος: | Discovering Genome-Wide Tag SNPs Based on the Mutual Information of the Variants |
|---|---|
| Συγγραφείς: | Elmas, Abdulkadir, Ou Yang, Tai-Hsien, Wang, Xiaodong, Anastassiou, Dimitris |
| Στοιχεία εκδότη: | Public Library of Science |
| Έτος έκδοσης: | 2016 |
| Συλλογή: | Columbia University: Academic Commons |
| Θεματικοί όροι: | Genomics--Data processing, Human genetics--Data processing, Chromosomes, Gene mapping, Single nucleotide polymorphisms, Genetics, Biology--Classification |
| Περιγραφή: | Exploring linkage disequilibrium (LD) patterns among the single nucleotide polymorphism (SNP) sites can improve the accuracy and cost-effectiveness of genomic association studies, whereby representative (tag) SNPs are identified to sufficiently represent the genomic diversity in populations. There has been considerable amount of effort in developing efficient algorithms to select tag SNPs from the growing large-scale data sets. Methods using the classical pairwise-LD and multi-locus LD measures have been proposed that aim to reduce the computational complexity and to increase the accuracy, respectively. The present work solves the tag SNP selection problem by efficiently balancing the computational complexity and accuracy, and improves the coverage in genomic diversity in a cost-effective manner. The employed algorithm makes use of mutual information to explore the multi-locus association between SNPs and can handle different data types and conditions. Experiments with benchmark HapMap data sets show comparable or better performance against the state-of-the-art algorithms. In particular, as a novel application, the genome-wide SNP tagging is performed in the 1000 Genomes Project data sets, and produced a well-annotated database of tagging variants that capture the common genotype diversity in 2,504 samples from 26 human populations. Compared to conventional methods, the algorithm requires as input only the genotype (or haplotype) sequences, can scale up to genome-wide analyses, and produces accurate solutions with more information-rich output, providing an improved platform for researchers towards the subsequent association studies. |
| Τύπος εγγράφου: | article in journal/newspaper |
| Γλώσσα: | English |
| Relation: | https://doi.org/10.7916/D8WW7PCX |
| DOI: | 10.7916/D8WW7PCX |
| Διαθεσιμότητα: | https://doi.org/10.7916/D8WW7PCX |
| Αριθμός Καταχώρησης: | edsbas.4DB076A7 |
| Βάση Δεδομένων: | BASE |
| FullText | Text: Availability: 0 CustomLinks: – Url: https://doi.org/10.7916/D8WW7PCX# Name: EDS - BASE (ns324271) Category: fullText Text: View record from BASE |
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| Items | – Name: Title Label: Title Group: Ti Data: Discovering Genome-Wide Tag SNPs Based on the Mutual Information of the Variants – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Elmas%2C+Abdulkadir%22">Elmas, Abdulkadir</searchLink><br /><searchLink fieldCode="AR" term="%22Ou+Yang%2C+Tai-Hsien%22">Ou Yang, Tai-Hsien</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Xiaodong%22">Wang, Xiaodong</searchLink><br /><searchLink fieldCode="AR" term="%22Anastassiou%2C+Dimitris%22">Anastassiou, Dimitris</searchLink> – Name: Publisher Label: Publisher Information Group: PubInfo Data: Public Library of Science – Name: DatePubCY Label: Publication Year Group: Date Data: 2016 – Name: Subset Label: Collection Group: HoldingsInfo Data: Columbia University: Academic Commons – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Genomics--Data+processing%22">Genomics--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Human+genetics--Data+processing%22">Human genetics--Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Chromosomes%22">Chromosomes</searchLink><br /><searchLink fieldCode="DE" term="%22Gene+mapping%22">Gene mapping</searchLink><br /><searchLink fieldCode="DE" term="%22Single+nucleotide+polymorphisms%22">Single nucleotide polymorphisms</searchLink><br /><searchLink fieldCode="DE" term="%22Genetics%22">Genetics</searchLink><br /><searchLink fieldCode="DE" term="%22Biology--Classification%22">Biology--Classification</searchLink> – Name: Abstract Label: Description Group: Ab Data: Exploring linkage disequilibrium (LD) patterns among the single nucleotide polymorphism (SNP) sites can improve the accuracy and cost-effectiveness of genomic association studies, whereby representative (tag) SNPs are identified to sufficiently represent the genomic diversity in populations. There has been considerable amount of effort in developing efficient algorithms to select tag SNPs from the growing large-scale data sets. Methods using the classical pairwise-LD and multi-locus LD measures have been proposed that aim to reduce the computational complexity and to increase the accuracy, respectively. The present work solves the tag SNP selection problem by efficiently balancing the computational complexity and accuracy, and improves the coverage in genomic diversity in a cost-effective manner. The employed algorithm makes use of mutual information to explore the multi-locus association between SNPs and can handle different data types and conditions. Experiments with benchmark HapMap data sets show comparable or better performance against the state-of-the-art algorithms. In particular, as a novel application, the genome-wide SNP tagging is performed in the 1000 Genomes Project data sets, and produced a well-annotated database of tagging variants that capture the common genotype diversity in 2,504 samples from 26 human populations. Compared to conventional methods, the algorithm requires as input only the genotype (or haplotype) sequences, can scale up to genome-wide analyses, and produces accurate solutions with more information-rich output, providing an improved platform for researchers towards the subsequent association studies. – Name: TypeDocument Label: Document Type Group: TypDoc Data: article in journal/newspaper – Name: Language Label: Language Group: Lang Data: English – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: https://doi.org/10.7916/D8WW7PCX – Name: DOI Label: DOI Group: ID Data: 10.7916/D8WW7PCX – Name: URL Label: Availability Group: URL Data: https://doi.org/10.7916/D8WW7PCX – Name: AN Label: Accession Number Group: ID Data: edsbas.4DB076A7 |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.7916/D8WW7PCX Languages: – Text: English Subjects: – SubjectFull: Genomics--Data processing Type: general – SubjectFull: Human genetics--Data processing Type: general – SubjectFull: Chromosomes Type: general – SubjectFull: Gene mapping Type: general – SubjectFull: Single nucleotide polymorphisms Type: general – SubjectFull: Genetics Type: general – SubjectFull: Biology--Classification Type: general Titles: – TitleFull: Discovering Genome-Wide Tag SNPs Based on the Mutual Information of the Variants Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Elmas, Abdulkadir – PersonEntity: Name: NameFull: Ou Yang, Tai-Hsien – PersonEntity: Name: NameFull: Wang, Xiaodong – PersonEntity: Name: NameFull: Anastassiou, Dimitris IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2016 Identifiers: – Type: issn-locals Value: edsbas – Type: issn-locals Value: edsbas.oa |
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