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定制阵列比较基因组杂交:DNA质量、专业眼光及变异验证的重要性

Custom Array Comparative Genomic Hybridization: the Importance of DNA Quality, an Expert Eye, and Variant Validation.

作者信息

Lantieri Francesca, Malacarne Michela, Gimelli Stefania, Santamaria Giuseppe, Coviello Domenico, Ceccherini Isabella

机构信息

Dipartimento di Scienzedella Salute, Sezione di Biostatistica, Università degli Studi di Genova, Via Pastore 1, 16132 Genoa, Italy.

Struttura Complessa Laboratorio Genetica Umana, E.O. Ospedali Galliera, Via Volta 6, 16128 Genoa, Italy.

出版信息

Int J Mol Sci. 2017 Mar 10;18(3):609. doi: 10.3390/ijms18030609.

DOI:10.3390/ijms18030609
PMID:28287439
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5372625/
Abstract

The presence of false positive and false negative results in the Array Comparative Genomic Hybridization (aCGH) design is poorly addressed in literature reports. We took advantage of a custom aCGH recently carried out to analyze its design performance, the use of several Agilent aberrations detection algorithms, and the presence of false results. Our study provides a confirmation that the high density design does not generate more noise than standard designs and, might reach a good resolution. We noticed a not negligible presence of false negative and false positive results in the imbalances call performed by the Agilent software. The Aberration Detection Method 2 (ADM-2) algorithm with a threshold of 6 performed quite well, and the array design proved to be reliable, provided that some additional filters are applied, such as considering only intervals with average absolute log₂ratio above 0.3. We also propose an additional filter that takes into account the proportion of probes with log₂ratio exceeding suggestive values for gain or loss. In addition, the quality of samples was confirmed to be a crucial parameter. Finally, this work raises the importance of evaluating the samples profiles by eye and the necessity of validating the imbalances detected.

摘要

在阵列比较基因组杂交(aCGH)设计中,假阳性和假阴性结果的存在在文献报道中很少被提及。我们利用最近进行的一项定制aCGH来分析其设计性能、几种安捷伦异常检测算法的使用情况以及假结果的存在情况。我们的研究证实,高密度设计产生的噪声并不比标准设计多,并且可能达到良好的分辨率。我们注意到,在安捷伦软件进行的不平衡调用中,假阴性和假阳性结果的存在不可忽视。阈值为6的异常检测方法2(ADM-2)算法表现相当不错,并且阵列设计被证明是可靠的,前提是应用一些额外的过滤器,例如仅考虑平均绝对log₂比值高于0.3的区间。我们还提出了一种额外的过滤器,该过滤器考虑了log₂比值超过增益或损失提示值的探针比例。此外,样本质量被确认为一个关键参数。最后,这项工作凸显了通过目视评估样本概况的重要性以及验证检测到的不平衡的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4800/5372625/f6fa4853271d/ijms-18-00609-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4800/5372625/97615b8a6e0f/ijms-18-00609-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4800/5372625/6dd746e8e44b/ijms-18-00609-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4800/5372625/f6fa4853271d/ijms-18-00609-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4800/5372625/97615b8a6e0f/ijms-18-00609-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4800/5372625/6dd746e8e44b/ijms-18-00609-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4800/5372625/f6fa4853271d/ijms-18-00609-g003.jpg

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