title: MDQC: a new quality assessment method for microarrays based on quality control reports.
abstract: BACKGROUND
  The process of producing microarray data involves multiple steps, some of which may suffer from technical problems and seriously damage the quality of the data. Thus, it is essential to identify those arrays with low quality. This article addresses two questions: (1) how to assess the quality of a microarray dataset using the measures provided in quality control (QC) reports; (2) how to identify possible sources of the quality problems.
  
  
  RESULTS
  We propose a novel multivariate approach to evaluate the quality of an array that examines the 'Mahalanobis distance' of its quality attributes from those of other arrays. Thus, we call it Mahalanobis Distance Quality Control (MDQC) and examine different approaches of this method. MDQC flags problematic arrays based on the idea of outlier detection, i.e. it flags those arrays whose quality attributes jointly depart from those of the bulk of the data. Using two case studies, we show that a multivariate analysis gives substantially richer information than analyzing each parameter of the QC report in isolation. Moreover, once the QC report is produced, our quality assessment method is computationally inexpensive and the results can be easily visualized and interpreted. Finally, we show that computing these distances on subsets of the quality measures in the report may increase the method's ability to detect unusual arrays and helps to identify possible reasons of the quality problems.
  
  
  BACKGROUND
  The library to implement MDQC will soon be available from Bioconductor.
authors.affiliation: Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada. gcohen@mrl.ubc.ca
authors.forename: Gabriela V
authors.initials: GV
authors.lastname: Cohen Freue
authors.forename: Zsuzsanna
authors.initials: Z
authors.lastname: Hollander
authors.forename: Enqing
authors.initials: E
authors.lastname: Shen
authors.forename: Ruben H
authors.initials: RH
authors.lastname: Zamar
authors.forename: Robert
authors.initials: R
authors.lastname: Balshaw
authors.forename: Andreas
authors.initials: A
authors.lastname: Scherer
authors.forename: Bruce
authors.initials: B
authors.lastname: McManus
authors.forename: Paul
authors.initials: P
authors.lastname: Keown
authors.forename: W Robert
authors.initials: WR
authors.lastname: McMaster
authors.forename: Raymond T
authors.initials: RT
authors.lastname: Ng
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D015999:Multivariate Analysis; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D011786:Quality Control; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity