title: Equalizer reduces SNP bias in Affymetrix microarrays.
abstract: BACKGROUND
  Gene expression microarrays measure the levels of messenger ribonucleic acid (mRNA) in a sample using probe sequences that hybridize with transcribed regions. These probe sequences are designed using a reference genome for the relevant species. However, most model organisms and all humans have genomes that deviate from their reference. These variations, which include single nucleotide polymorphisms, insertions of additional nucleotides, and nucleotide deletions, can affect the microarray's performance. Genetic experiments comparing individuals bearing different population-associated single nucleotide polymorphisms that intersect microarray probes are therefore subject to systemic bias, as the reduction in binding efficiency due to a technical artifact is confounded with genetic differences between parental strains. This problem has been recognized for some time, and earlier methods of compensation have attempted to identify probes affected by genome variants using statistical models. These methods may require replicate microarray measurement of gene expression in the relevant tissue in inbred parental samples, which are not always available in model organisms and are never available in humans.
  
  
  RESULTS
  By using sequence information for the genomes of organisms under investigation, potentially problematic probes can now be identified a priori. However, there is no published software tool that makes it easy to eliminate these probes from an annotation. I present equalizer, a software package that uses genome variant data to modify annotation files for the commonly used Affymetrix IVT and Gene/Exon platforms. These files can be used by any microarray normalization method for subsequent analysis. I demonstrate how use of equalizer on experiments mapping germline influence on gene expression in a genetic cross between two divergent mouse species and in human samples significantly reduces probe hybridization-induced bias, reducing false positive and false negative findings.
  
  
  CONCLUSIONS
  The equalizer package reduces probe hybridization bias from experiments performed on the Affymetrix microarray platform, allowing accurate assessment of germline influence on gene expression.
authors.affiliation: Helen Diller Family Comprehensive Cancer Center, University of California at San Francisco, San Francisco, CA, 94158, USA. David.Quigley@ucsf.edu.
authors.forename: David
authors.initials: D
authors.lastname: Quigley
mesh_terms: D000818:Animals; D002460:Cell Line; D005260:Female; D020869:Gene Expression Profiling; D016678:Genome; D006801:Humans; D008321:Mammary Glands, Animal / Q000378:metabolism; D051379:Mice; D009693:Nucleic Acid Hybridization; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D012333:RNA, Messenger / Q000378:metabolism; D012867:Skin / Q000378:metabolism; D012984:Software
chemical_list: D012333:RNA, Messenger