title: Use of autocorrelation scanning in DNA copy number analysis.
abstract: BACKGROUND
  Data quality is a critical issue in the analyses of DNA copy number alterations obtained from microarrays. It is commonly assumed that copy number alteration data can be modeled as piecewise constant and the measurement errors of different probes are independent. However, these assumptions do not always hold in practice. In some published datasets, we find that measurement errors are highly correlated between probes that interrogate nearby genomic loci, and the piecewise-constant model does not fit the data well. The correlated errors cause problems in downstream analysis, leading to a large number of DNA segments falsely identified as having copy number gains and losses.
  
  
  METHODS
  We developed a simple tool, called autocorrelation scanning profile, to assess the dependence of measurement error between neighboring probes.
  
  
  RESULTS
  Autocorrelation scanning profile can be used to check data quality and refine the analysis of DNA copy number data, which we demonstrate in some typical datasets.
  
  
  BACKGROUND
  lzhangli@mdanderson.org.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA and Department of Biophysics, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
authors.forename: Liangcai
authors.initials: L
authors.lastname: Zhang
authors.forename: Li
authors.initials: L
authors.lastname: Zhang
mesh_terms: D056915:DNA Copy Number Variations; D003627:Data Interpretation, Statistical; D016678:Genome; D023281:Genomics / Q000379:methods
references.citation: Bioinformatics. 2011 Sep 1;27(17):2338-45
references.pmid: 21752800
references.citation: Bioinformatics. 2009 Jul 1;25(13):1669-79
references.pmid: 19389735
references.citation: Bioinformatics. 2011 Mar 1;27(5):678-85
references.pmid: 21183584
references.citation: BioData Min. 2011 Apr 13;4:8
references.pmid: 21489293
references.citation: Haematologica. 2007 Jun;92(6):795-802
references.pmid: 17550852
references.citation: Clin Cancer Res. 2009 Apr 15;15(8):2685-94
references.pmid: 19336518
references.citation: Bioinformatics. 2006 Apr 15;22(8):911-8
references.pmid: 16455750
references.citation: Genome Res. 2007 Nov;17(11):1665-74
references.pmid: 17921354
references.citation: Nat Genet. 2001 Nov;29(3):263-4
references.pmid: 11687795
references.citation: PLoS One. 2011;6(8):e23543
references.pmid: 21858162
references.citation: Clin Genet. 2007 Nov;72(5):441-7
references.pmid: 17935507
references.citation: BMC Bioinformatics. 2010 Jul 16;11:380
references.pmid: 20637081
references.citation: Cell. 2012 Jan 20;148(1-2):29-32
references.pmid: 22265399
references.citation: Bioinformatics. 2012 Feb 15;28(4):470-8
references.pmid: 22199393
references.citation: Nat Genet. 2008 Oct;40(10):1166-74
references.pmid: 18776908
references.citation: J Pathol. 2010 Aug;221(4):411-24
references.pmid: 20593488
references.citation: Nat Genet. 2008 Jun;40(6):722-9
references.pmid: 18438408
references.citation: BMC Genomics. 2009 Nov 28;10:561
references.pmid: 19943955
references.citation: Bioinformatics. 2004 Dec 12;20(18):3413-22
references.pmid: 15381628
references.citation: Nat Methods. 2009 Jan;6(1):99-103
references.pmid: 19043412
references.citation: Cell. 2011 Mar 4;144(5):646-74
references.pmid: 21376230
references.citation: Eur J Hum Genet. 2012 Feb;20(2):161-5
references.pmid: 21934709
references.citation: Proc Natl Acad Sci U S A. 2011 Nov 15;108(46):E1128-36
references.pmid: 22065754
references.citation: BMC Bioinformatics. 2007 Oct 02;8:368
references.pmid: 17910767
references.citation: Bioinformatics. 2011 Oct 1;27(19):2648-54
references.pmid: 21828086
references.citation: Annu Rev Genet. 2011;45:203-26
references.pmid: 21854229
references.citation: Bioinformatics. 2010 Dec 15;26(24):3051-8
references.pmid: 20966003
references.citation: Biostatistics. 2004 Oct;5(4):557-72
references.pmid: 15475419
references.citation: Cytogenet Genome Res. 2008;123(1-4):307-12
references.pmid: 19287169
references.citation: Nucleic Acids Res. 2011 Jul;39(12):4928-41
references.pmid: 21398628
references.citation: PLoS One. 2011 Jan 13;6(1):e14511
references.pmid: 21249187
references.citation: BMC Bioinformatics. 2011 May 31;12:220
references.pmid: 21627824
references.citation: Bioinformatics. 2012 May 15;28(10):1307-13
references.pmid: 22474122
references.citation: Curr Med Chem. 2012;19(22):3739-47
references.pmid: 22680919
references.citation: BMC Bioinformatics. 2008 Apr 21;9:204
references.pmid: 18426588
references.citation: Genome Res. 2006 Sep;16(9):1149-58
references.pmid: 16899652
references.citation: Bioinformatics. 2012 Nov 1;28(21):2711-8
references.pmid: 22942022
references.citation: Genome Res. 2011 Jun;21(6):974-84
references.pmid: 21324876
references.citation: Nat Genet. 2007 Jul;39(7 Suppl):S37-42
references.pmid: 17597780
references.citation: Neuro Oncol. 2011 Feb;13(2):212-22
references.pmid: 21138945
references.citation: Adv Genet. 2008;60:107-39
references.pmid: 18358318
references.citation: PLoS One. 2012;7(4):e32396
references.pmid: 22523537
references.citation: Nucleic Acids Res. 2011 May;39(10):e65
references.pmid: 21321017
references.citation: BMC Med Genomics. 2011 Jan 26;4:14
references.pmid: 21269491
references.citation: Bioinformatics. 2005 Oct 15;21(20):3811-7
references.pmid: 16131523
references.citation: BMC Med Genomics. 2012 Jun 12;5:24
references.pmid: 22691279
references.citation: J Pathol. 2010 May;221(1):96-105
references.pmid: 20217874
references.citation: Bioinformatics. 2007 Apr 1;23(7):892-4
references.pmid: 17267432
references.citation: Genome Res. 2006 Dec;16(12):1465-79
references.pmid: 17142309