A self-tuning method for one-chip SNP identification.
Identifieur interne : 002360 ( PubMed/Corpus ); précédent : 002359; suivant : 002361A self-tuning method for one-chip SNP identification.
Auteurs : Michael Molla ; Jude Shavlik ; Todd Richmond ; Steven SmithSource :
- Proceedings. IEEE Computational Systems Bioinformatics Conference [ 1551-7497 ] ; 2004.
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Abstract
Current methods for interpreting oligonucleotide-based SNP-detection microarrays, SNP chips, are based on statistics and require extensive parameter tuning as well as extremely high-resolution images of the chip being processed. We present a method, based on a simple data-classification technique called nearest-neighbors that, on haploid organisms, produces results comparable to the published results of the leading statistical methods and requires very little in the way of parameter tuning. Furthermore, it can interpret SNP chips using lower-resolution scanners of the type more typically used in current microarray experiments. Along with our algorithm, we present the results of a SNP-detection experiment where, when independently applying this algorithm to six identical SARS SNP chips, we correctly identify all 24 SNPs in a particular strain of the SARS virus, with between 6 and 13 false positives across the six experiments.
DOI: 10.1109/csb.2004.1332419
PubMed: 16448001
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IEEE Computational Systems Bioinformatics Conference</title><idno type="ISSN">1551-7497</idno><imprint><date when="2004" type="published">2004</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Chromosome Mapping (methods)</term><term>DNA Mutational Analysis (methods)</term><term>Oligonucleotide Array Sequence Analysis (methods)</term><term>Pattern Recognition, Automated (methods)</term><term>Polymorphism, Single Nucleotide (genetics)</term><term>Sequence Alignment (methods)</term><term>Sequence Analysis, DNA (methods)</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Polymorphism, Single Nucleotide</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Chromosome Mapping</term><term>DNA Mutational Analysis</term><term>Oligonucleotide Array Sequence Analysis</term><term>Pattern Recognition, Automated</term><term>Sequence Alignment</term><term>Sequence Analysis, DNA</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Current methods for interpreting oligonucleotide-based SNP-detection microarrays, SNP chips, are based on statistics and require extensive parameter tuning as well as extremely high-resolution images of the chip being processed. We present a method, based on a simple data-classification technique called nearest-neighbors that, on haploid organisms, produces results comparable to the published results of the leading statistical methods and requires very little in the way of parameter tuning. Furthermore, it can interpret SNP chips using lower-resolution scanners of the type more typically used in current microarray experiments. Along with our algorithm, we present the results of a SNP-detection experiment where, when independently applying this algorithm to six identical SARS SNP chips, we correctly identify all 24 SNPs in a particular strain of the SARS virus, with between 6 and 13 false positives across the six experiments.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">16448001</PMID><DateCompleted><Year>2006</Year><Month>07</Month><Day>17</Day></DateCompleted><DateRevised><Year>2019</Year><Month>11</Month><Day>09</Day></DateRevised><Article PubModel="Print"><Journal><ISSN IssnType="Print">1551-7497</ISSN><JournalIssue CitedMedium="Print"><PubDate><Year>2004</Year></PubDate></JournalIssue><Title>Proceedings. 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Along with our algorithm, we present the results of a SNP-detection experiment where, when independently applying this algorithm to six identical SARS SNP chips, we correctly identify all 24 SNPs in a particular strain of the SARS virus, with between 6 and 13 false positives across the six experiments.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Molla</LastName><ForeName>Michael</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>University of Wisconsin-Madison, USA. molla.shavlik@cs.wisc.edu</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Shavlik</LastName><ForeName>Jude</ForeName><Initials>J</Initials></Author><Author ValidYN="Y"><LastName>Richmond</LastName><ForeName>Todd</ForeName><Initials>T</Initials></Author><Author ValidYN="Y"><LastName>Smith</LastName><ForeName>Steven</ForeName><Initials>S</Initials></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>1 R01 LM07050-01</GrantID><Acronym>LM</Acronym><Agency>NLM NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>5 T32 GM08349</GrantID><Acronym>GM</Acronym><Agency>NIGMS NIH HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType></PublicationTypeList></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Proc IEEE Comput Syst Bioinform Conf</MedlineTA><NlmUniqueID>101240586</NlmUniqueID><ISSNLinking>1551-7497</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D000465" MajorTopicYN="Y">Algorithms</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D002874" MajorTopicYN="N">Chromosome Mapping</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D004252" MajorTopicYN="N">DNA Mutational Analysis</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D020411" MajorTopicYN="N">Oligonucleotide Array Sequence Analysis</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D010363" MajorTopicYN="N">Pattern Recognition, Automated</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D020641" MajorTopicYN="N">Polymorphism, Single Nucleotide</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="Y">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D016415" MajorTopicYN="N">Sequence Alignment</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D017422" MajorTopicYN="N">Sequence Analysis, DNA</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="pubmed"><Year>2006</Year><Month>2</Month><Day>2</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2006</Year><Month>7</Month><Day>18</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2006</Year><Month>2</Month><Day>2</Day><Hour>9</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">16448001</ArticleId><ArticleId IdType="doi">10.1109/csb.2004.1332419</ArticleId></ArticleIdList></PubmedData></pubmed></record>Pour manipuler ce document sous Unix (Dilib)
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