Increasing the discovery power of -omics studies

Djork-Arné Clevert, Andreas Mayr, Andreas Mitterecker, Günter Klambauer, Armand Valsesia, Karl Forner, Marianne Tuefferd, Willem Talloen, Jérôme Wojcik, Hinrich W.H. Göhlmann, Sepp Hochreiter

Research output: Contribution to journalArticlepeer-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. 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 in analyzing -omics data are caused by an increased false detection rate (FDR) in measurements, like falsely detected DNA copy number changes, or falsely identified differentially expressed genes. The false detections are random and, therefore, not related to the tested conditions. Thus, a high FDR considerably decreases the discovery power of studies, especially if different -omics data are involved.
Original languageEnglish
Number of pages15
JournalSystems Biomedicine
Volume1
Issue number2
DOIs
Publication statusPublished - Apr 2013

Fields of science

  • 303 Health Sciences
  • 304 Medical Biotechnology
  • 305 Other Human Medicine, Health Sciences
  • 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
  • 301 Medical-Theoretical Sciences, Pharmacy
  • 302 Clinical Medicine
  • 106005 Bioinformatics

JKU Focus areas

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

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