LOX: Inferring level of expression from diverse methods of census sequencing

Zhang Zhang, Francesc Francisco López-Giráldez, Jeffrey P. Townsend

Research output: Contribution to journalArticlepeer-review

28 Scopus citations

Abstract

Summary: We present LOX (Level Of eXpression) that estimates the Level Of gene eXpression from high-throughput-expressed sequence datasets with multiple treatments or samples. Unlike most analyses, LOX incorporates a gene bias model that facilitates integration of diverse transcriptomic sequencing data that arises when transcriptomic data have been produced using diverse experimental methodologies. LOX integrates overall sequence count tallies normalized by total expressed sequence count to provide expression levels for each gene relative to all treatments as well as Bayesian credible intervals. © The Author 2010. Published by Oxford University Press. All rights reserved.
Original languageEnglish (US)
Pages (from-to)1918-1919
Number of pages2
JournalBioinformatics
Volume26
Issue number15
DOIs
StatePublished - Jun 10 2010

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01

ASJC Scopus subject areas

  • Biochemistry
  • Computational Theory and Mathematics
  • Computational Mathematics
  • Molecular Biology
  • Statistics and Probability
  • Computer Science Applications

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