S-score: A novel scoring method of gene signatures for molecular classification

Hung IHarry Chen, Tzu Hung Hsiao, Yidong Chen, Charles Keller

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Gene signatures have been utilized to discover the inferred biological functions under gene expression profiles.We present a novel sample scoring method called Signature-score (S-score). S-score quantifies the expression pattern by using gene signatures and has better accuracy and robustness than other scoring methods. A confidence boundary of S-score is determined to identify the status of samples for which gene signatures represent. Through the quantitative and qualitative analyses of S-score,we will be able to unambiguously identify the qualitative status of enriched pathways or biological processes. This scoring method will not only allow researchers to explore novel functions for microarray studies, but also to focus on known biological functions that manifest the phenotype.

Original languageEnglish (US)
Title of host publicationProceedings 2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
PublisherIEEE Computer Society
Pages154-157
Number of pages4
ISBN (Print)9781467304900
DOIs
StatePublished - 2011
Event2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11 - San Antonio, TX, United States
Duration: Dec 4 2011Dec 6 2011

Publication series

NameProceedings - IEEE International Workshop on Genomic Signal Processing and Statistics
ISSN (Print)2150-3001
ISSN (Electronic)2150-301X

Other

Other2011 IEEE International Workshop on Genomic Signal Processing and Statistics, GENSIPS'11
Country/TerritoryUnited States
CitySan Antonio, TX
Period12/4/1112/6/11

Keywords

  • Classification
  • Gene signature
  • Pathway analysis

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Computational Theory and Mathematics
  • Biomedical Engineering
  • Signal Processing

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