CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays.
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 m...
| Publicado en: | Journal of Biomedical Informatics Vol. 54; pp. 106 - 114 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Academic Press Inc.
Apr2015
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109726504&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109726504 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15320464 OMB jtl: Journal of Biomedical Informatics issn: 15320464 maglogo: N pubinfo: dt: Apr2015 vid: 54 pid: 735 pub: Academic Press Inc. place: Burlington, Massachusetts artinfo: ui: 109726504 NLM25595567 2012984842 10.1016/j.jbi.2015.01.001 NLM25595567 PMC4936396 109726504 ppf: 106 ppct: 8 formats: tig: atl: CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays. aug: au: Goodman, Corey W Major, Heather J Walls, William D Sheffield, Val C Casavant, Thomas L Darbro, Benjamin W sug: ab: 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. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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