Correct microarray analysis approaches in 'Hsa-circRNA11783-2 in peripheral blood is correlated with coronary artery disease and type 2 diabetes mellitus'

被引：10

作者：

Li, Chenyu ^{[1
]}

Zhao, Long ^{[1
]}

Jiang, Wei ^{[1
]}

Che, Lin ^{[1
]}

Xu, Yan ^{[1
]}

机构：

[1] Qingdao Univ, Dept Nephrol, Affiliated Hosp, 16 Jiangsu Rd, Qingdao 266003, Peoples R China

来源：

DIABETES & VASCULAR DISEASE RESEARCH | 2018年 / 15卷 / 01期

关键词：

Bioinformatics; microarray analysis; statistics; circular RNA;

D O I：

10.1177/1479164117739435

中图分类号：

R5 [内科学];

学科分类号：

1002 ; 100201 ;

摘要：

We read with great interest the article by Li et al. The results are illuminating for understanding the relationship among Hsa-circRNA11783-2, coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM). However, from our perspective, the bioinformatics analyses need further context as the statistics for differential fold changes in expression data are not explained fully. The authors seem to use unadjusted p values for detecting differentially expressed circular RNA (differentially expressed genes (DEGs)) between the control, CAD and T2DM group. Due to the high false positives caused by a large number of probes and multiple comparisons, it seems essential to analyse microarray data properly to reach a reliable result by a statistical method. Only selecting circular RNA with greater than two fold change with unadjusted p values < 0.05 in expression is not reliable and suitable for high-level microarray analysis.

引用

页码：92 / 93

页数：2

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