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CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays
Journal article   Open access   Peer reviewed

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays

Corey W Goodman, Heather J Major, William D Walls, Val C Sheffield, Thomas L Casavant and Benjamin W Darbro
Journal of biomedical informatics, Vol.54, pp.106-113
04/2015
DOI: 10.1016/j.jbi.2015.01.001
PMCID: PMC4936396
PMID: 25595567
url
https://doi.org/10.1016/j.jbi.2015.01.001View
Published (Version of record) Open Access

Abstract

[Display omitted] •Chromosomal microarrays (CMAs) are important research and diagnostic tools.•CNV-ROC is a software tool that can aid in the evaluation of CMA platforms.•CNV-ROC uses a per-probe approach for comparison of copy number variants (CNVs).•CNV-ROC calculates genome-wide true and false positive and negative results.•CNV-ROC can use both unique and common, polymorphic CNVs. 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.
Sensitivity Specificity Microarray Precision ROC

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