title: Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction.
abstract: BACKGROUND
  Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a "gold standard". We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods.
  
  
  RESULTS
  Expression of sex-chromosome genes were used as true internal biological controls to compare alternate probe-level data extraction algorithms (Microarray Suite 5.0 [MAS5.0], Model Based Expression Index [MBEI] and Robust Multi-array Average [RMA]), to assess microarray data quality and to establish some statistical guidelines for analyzing large-scale gene expression. These approaches were implemented on a large new dataset of human brain samples. RMA-generated gene expression values were markedly less variable and more reliable than MAS5.0 and MBEI-derived values. A statistical technique controlling the false discovery rate was applied to adjust for multiple testing, as an alternative to the Bonferroni method, and showed no evidence of false negative results. Fourteen probesets, representing nine Y- and two X-chromosome linked genes, displayed significant sex differences in brain prefrontal cortex gene expression.
  
  
  CONCLUSIONS
  In this study, we have demonstrated the use of sex genes as true biological internal controls for genomic analysis of complex tissues, and suggested analytical guidelines for testing alternate oligonucleotide microarray data extraction protocols and for adjusting multiple statistical analysis of differentially expressed genes. Our results also provided evidence for sex differences in gene expression in the brain prefrontal cortex, supporting the notion of a putative direct role of sex-chromosome genes in differentiation and maintenance of sexual dimorphism of the central nervous system. Importantly, these analytical approaches are applicable to all microarray studies that include male and female human or animal subjects.
authors.affiliation: Department of Neuroscience, New York State Psychiatric Institute, New York, NY 10032, USA. hanga@neuron.cpmc.columbia.edu
authors.forename: Hanga C
authors.initials: HC
authors.lastname: Galfalvy
authors.forename: Loubna
authors.initials: L
authors.lastname: Erraji-Benchekroun
authors.forename: Peggy
authors.initials: P
authors.lastname: Smyrniotopoulos
authors.forename: Paul
authors.initials: P
authors.lastname: Pavlidis
authors.forename: Steven P
authors.initials: SP
authors.lastname: Ellis
authors.forename: J John
authors.initials: JJ
authors.lastname: Mann
authors.forename: Etienne
authors.initials: E
authors.lastname: Sibille
authors.forename: Victoria
authors.initials: V
authors.lastname: Arango
mesh_terms: D000465:Algorithms; D041322:Chromosomes, Human, Y / Q000235:genetics; D019295:Computational Biology / Q000379:methods / Q000706:statistics & numerical data; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods / Q000706:statistics & numerical data; D018507:Gene Expression Regulation, Developmental / Q000235:genetics; D008040:Genetic Linkage / Q000235:genetics; D023281:Genomics / Q000379:methods*; D006801:Humans; D008297:Male; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods / Q000706:statistics & numerical data; D017397:Prefrontal Cortex / Q000737:chemistry*; D011786:Quality Control; D015347:RNA Probes / Q000235:genetics*; D012680:Sensitivity and Specificity; D012730:Sex Chromosomes / Q000235:genetics; D012733:Sex Differentiation / Q000235:genetics*
chemical_list: D015347:RNA Probes