LOX: inferring Level Of eXpression from diverse methods of census sequencing.

Zhang Zhang, Francesc López-Giráldez, Jeffrey P Townsend
Author Information
  1. Zhang Zhang: Department of Ecology and Evolutionary Biology and Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.

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.
AVAILABILITY: http://www.yale.edu/townsend/software.html

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Grants

  1. P01 GM068087-06/NIGMS NIH HHS
  2. P01 GM068087/NIGMS NIH HHS
  3. RR19895/NCRR NIH HHS
  4. P01 GM068087-06S1/NIGMS NIH HHS
  5. P01 GM 068087/NIGMS NIH HHS
  6. P01 GM068087-08/NIGMS NIH HHS
  7. P01 GM068087-07/NIGMS NIH HHS

MeSH Term

Computational Biology
Expressed Sequence Tags
Gene Expression Profiling
Gene Expression Regulation, Fungal
Oligonucleotide Array Sequence Analysis
Software

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