评估miRNA微阵列平台之间的一致性。

Niccolò P Bassani, Federico Ambrogi, Elia M Biganzoli
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引用次数: 6

摘要

在过去的几年中,miRNA微阵列平台为几种疾病发生和发展的生物学机制提供了很好的见解。然而,只有少数研究使用考虑数据测量误差的方法评估了不同微阵列平台之间的一致性。在这项工作中,我们建议使用改进版本的Bland-Altman图来评估微阵列平台之间的一致性。为此,使用三种不同的miRNA平台(Affymetrix, Agilent, Illumina)在三重复阵列上分析了两个样本,一个肾肿瘤细胞系和20个不同的人类正常组织。通过计算技术重复之间的成对一致性相关系数(CCC)和总体一致性相关系数(OCCC)以及bootstrap百分位数置信区间来评估平台内的可靠性,结果显示两个样本的所有平台都具有中等至良好的可重复性。改进的Bland-Altman分析显示Agilent和Illumina的一致性模式良好,而Affymetrix对两个样本的一致性较差至中等。该方法可通过修改原始Bland-Altman图来评估阵列平台之间的一致性,以使其考虑测量误差和偏差校正,并可用于评估除miRNA微阵列以外的其他类型阵列之间的一致性模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Assessing Agreement between miRNA Microarray Platforms.

Assessing Agreement between miRNA Microarray Platforms.

Assessing Agreement between miRNA Microarray Platforms.

Assessing Agreement between miRNA Microarray Platforms.

Over the last few years, miRNA microarray platforms have provided great insights into the biological mechanisms underlying the onset and development of several diseases. However, only a few studies have evaluated the concordance between different microarray platforms using methods that took into account measurement error in the data. In this work, we propose the use of a modified version of the Bland-Altman plot to assess agreement between microarray platforms. To this aim, two samples, one renal tumor cell line and a pool of 20 different human normal tissues, were profiled using three different miRNA platforms (Affymetrix, Agilent, Illumina) on triplicate arrays. Intra-platform reliability was assessed by calculating pair-wise concordance correlation coefficients (CCC) between technical replicates and overall concordance correlation coefficient (OCCC) with bootstrap percentile confidence intervals, which revealed moderate-to-good repeatability of all platforms for both samples. Modified Bland-Altman analysis revealed good patterns of concordance for Agilent and Illumina, whereas Affymetrix showed poor-to-moderate agreement for both samples considered. The proposed method is useful to assess agreement between array platforms by modifying the original Bland-Altman plot to let it account for measurement error and bias correction and can be used to assess patterns of concordance between other kinds of arrays other than miRNA microarrays.

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来源期刊
自引率
0.00%
发文量
0
审稿时长
11 weeks
期刊介绍: High-Throughput (formerly Microarrays, ISSN 2076-3905) is a multidisciplinary peer-reviewed scientific journal that provides an advanced forum for the publication of studies reporting high-dimensional approaches and developments in Life Sciences, Chemistry and related fields. Our aim is to encourage scientists to publish their experimental and theoretical results based on high-throughput techniques as well as computational and statistical tools for data analysis and interpretation. The full experimental or methodological details must be provided so that the results can be reproduced. There is no restriction on the length of the papers. High-Throughput invites submissions covering several topics, including, but not limited to: Microarrays, DNA Sequencing, RNA Sequencing, Protein Identification and Quantification, Cell-based Approaches, Omics Technologies, Imaging, Bioinformatics, Computational Biology/Chemistry, Statistics, Integrative Omics, Drug Discovery and Development, Microfluidics, Lab-on-a-chip, Data Mining, Databases, Multiplex Assays.
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