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Increasing the Discovery Power of -Omics Studies

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

Current clinical and biological studies apply different biotechnologies and subsequently combine the resulting -omics data to test biological hypotheses. The plethora of -omics data and their combination generates a large number of hypotheses and apparently increases the study power. In contrary to these expectations, the wealth of -omics data may even reduce the statistical power of a study because of a large correction factor for multiple testing. Typically this loss of power at -omics data is caused by an increased false detection rate (FDR) in single measurements like falsely detected DNA copy numbers or falsely identified differentially expressed genes. The false detections are likely to fail the test because they are random and, therefore, are not related to the tested conditions. Thus, a high FDR at the detection level considerably decreases the discovery power of studies, specifically if different -omics data are involved.
Original languageEnglish
Title of host publicationCAMDA 2012, Satellite Meeting of ISMB/ECCB 2012
Number of pages20
Publication statusPublished - 2012

Fields of science

  • 106013 Genetics
  • 106041 Structural biology
  • 102 Computer Sciences
  • 101029 Mathematical statistics
  • 102001 Artificial intelligence
  • 101004 Biomathematics
  • 102015 Information systems
  • 102018 Artificial neural networks
  • 106002 Biochemistry
  • 106023 Molecular biology
  • 305 Other Human Medicine, Health Sciences
  • 106005 Bioinformatics

JKU Focus areas

  • Computation in Informatics and Mathematics
  • Nano-, Bio- and Polymer-Systems: From Structure to Function

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