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微阵列探针集的选择:代表一个基因的最优微阵列探针集。

Jetset: selecting the optimal microarray probe set to represent a gene.

机构信息

Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark.

出版信息

BMC Bioinformatics. 2011 Dec 15;12:474. doi: 10.1186/1471-2105-12-474.

Abstract

BACKGROUND

Interpretation of gene expression microarrays requires a mapping from probe set to gene. On many Affymetrix gene expression microarrays, a given gene may be detected by multiple probe sets, which may deliver inconsistent or even contradictory measurements. Therefore, obtaining an unambiguous expression estimate of a pre-specified gene can be a nontrivial but essential task.

RESULTS

We developed scoring methods to assess each probe set for specificity, splice isoform coverage, and robustness against transcript degradation. We used these scores to select a single representative probe set for each gene, thus creating a simple one-to-one mapping between gene and probe set. To test this method, we evaluated concordance between protein measurements and gene expression values, and between sets of genes whose expression is known to be correlated. For both test cases, we identified genes that were nominally detected by multiple probe sets, and we found that the probe set chosen by our method showed stronger concordance.

CONCLUSIONS

This method provides a simple, unambiguous mapping to allow assessment of the expression levels of specific genes of interest.

摘要

背景

基因表达微阵列的解释需要从探针集到基因进行映射。在许多 Affymetrix 基因表达微阵列上,一个给定的基因可能会被多个探针集检测到,这些探针集可能会提供不一致甚至相互矛盾的测量结果。因此,获得指定基因的明确表达估计可能是一项非平凡但必不可少的任务。

结果

我们开发了评分方法来评估每个探针集的特异性、剪接异构体覆盖范围以及对转录物降解的稳健性。我们使用这些分数为每个基因选择一个代表性的探针集,从而在基因和探针集之间创建一个简单的一对一映射。为了测试这种方法,我们评估了蛋白质测量值和基因表达值之间的一致性,以及表达已知相关的基因集之间的一致性。在这两种情况下,我们都确定了多个探针集名义上检测到的基因,并且发现我们方法选择的探针集显示出更强的一致性。

结论

该方法提供了一种简单、明确的映射方法,可用于评估特定感兴趣基因的表达水平。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7145/3266307/356448a30508/1471-2105-12-474-1.jpg

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