title: CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays.
abstract: Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments.
authors.affiliation: Department of Electrical and Computer Engineering, The University of Iowa, United States; Center for Bioinformatics and Computational Biology, The University of Iowa, United States. Electronic address: corey-goodman@uiowa.edu.
authors.forename: Corey W
authors.initials: CW
authors.lastname: Goodman
authors.affiliation: Department of Pediatrics, The University of Iowa, United States. Electronic address: heather-major@uiowa.edu.
authors.forename: Heather J
authors.initials: HJ
authors.lastname: Major
authors.affiliation: Department of Electrical and Computer Engineering, The University of Iowa, United States; Center for Bioinformatics and Computational Biology, The University of Iowa, United States. Electronic address: daniel-walls@uiowa.edu.
authors.forename: William D
authors.initials: WD
authors.lastname: Walls
authors.affiliation: Ph.D. Program in Genetics, The University of Iowa, United States; Department of Pediatrics, The University of Iowa, United States. Electronic address: val-sheffield@uiowa.edu.
authors.forename: Val C
authors.initials: VC
authors.lastname: Sheffield
authors.affiliation: Department of Electrical and Computer Engineering, The University of Iowa, United States; Department of Biomedical Engineering, The University of Iowa, United States; Center for Bioinformatics and Computational Biology, The University of Iowa, United States; Ph.D. Program in Genetics, The University of Iowa, United States. Electronic address: tomc@eng.uiowa.edu.
authors.forename: Thomas L
authors.initials: TL
authors.lastname: Casavant
authors.affiliation: Department of Pediatrics, The University of Iowa, United States. Electronic address: benjamin-darbro@uiowa.edu.
authors.forename: Benjamin W
authors.initials: BW
authors.lastname: Darbro
mesh_terms: D000465:Algorithms; D004247:DNA / Q000032:analysis* / Q000235:genetics; D056915:DNA Copy Number Variations / Q000235:genetics*; D005260:Female; D006801:Humans; D008297:Male; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D020641:Polymorphism, Single Nucleotide; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D004247:DNA
keywords: Microarray; Precision; ROC; Sensitivity; Specificity