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<span style = 'font-size: large'> '''Collins, SR, Schuldiner, M, Krogan, NJ and Weissman, JS'''  (2006) A strategy for extracting and analyzing large-scale quantitative epistatic interaction data.''Genome Biol.'' '''7''':R63</span>
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|{{TableHeadingColor}} |'''Abstract''' || <protect>Recently, approaches have been developed for high-throughput identification of synthetic sick/lethal gene pairs. However, these are only a specific example of the broader phenomenon of epistasis, wherein the presence of one mutation modulates the phenotype of another. We present analysis techniques for generating high-confidence quantitative epistasis scores from measurements made using synthetic genetic array and epistatic miniarray profile (E-MAP) technology, as well as several tools for higher-level analysis of the resulting data that are greatly enhanced by the quantitative score and detection of alleviating interactions.</protect>
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'''No author listed''' (2006) A strategy for extracting and analyzing large-scale quantitative epistatic interaction data. ''Genome Biol.'' '''7''':R63
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!align=left  |Abstract
*  [http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=16859555 PubMed]
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Recently, approaches have been developed for high-throughput identification of synthetic sick/lethal gene pairs. However, these are only a specific example of the broader phenomenon of epistasis, wherein the presence of one mutation modulates the phenotype of another. We present analysis techniques for generating high-confidence quantitative epistasis scores from measurements made using synthetic genetic array and epistatic miniarray profile (E-MAP) technology, as well as several tools for higher-level analysis of the resulting data that are greatly enhanced by the quantitative score and detection of alleviating interactions.
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!align=left  |Links
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[http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=pubmed&dopt=Abstract&list_uids=16859555 PubMed] [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1779568 PMC1779568]
Online version:[http://dx.doi.org/10.1186/gb-2006-7-7-r63 10.1186/gb-2006-7-7-r63]
Online version:[http://dx.doi.org/10.1186/gb-2006-7-7-r63 10.1186/gb-2006-7-7-r63]
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!align=left  |Keywords
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Epistasis, Genetic; Mutation; Oligonucleotide Array Sequence Analysis; Phenotype
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==Significance {{HelpIcon|Help:Literature}} ==
==Significance {{HelpIcon|Help:Literature}} ==
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Revision as of 18:53, 1 September 2013

Citation

No author listed (2006) A strategy for extracting and analyzing large-scale quantitative epistatic interaction data. Genome Biol. 7:R63

Abstract

Recently, approaches have been developed for high-throughput identification of synthetic sick/lethal gene pairs. However, these are only a specific example of the broader phenomenon of epistasis, wherein the presence of one mutation modulates the phenotype of another. We present analysis techniques for generating high-confidence quantitative epistasis scores from measurements made using synthetic genetic array and epistatic miniarray profile (E-MAP) technology, as well as several tools for higher-level analysis of the resulting data that are greatly enhanced by the quantitative score and detection of alleviating interactions.

Links

PubMed PMC1779568 Online version:10.1186/gb-2006-7-7-r63

Keywords

Epistasis, Genetic; Mutation; Oligonucleotide Array Sequence Analysis; Phenotype

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