An approach to evaluate the reliability of hybridization-based and sequencing-based gene expression profiling technologies.
Hybridization-based and sequencing-based technologies have found a widespread application in gene expression profiling analysis but much ambiguity exists regarding their reliability. This study developed a framework based on three parameters: detection ability, repeatability, and accuracy to evaluate the reliability of gene expression profiling technologies. The fraction of coverage of detected transcript category, the degree of variance for the number of differentially expressed genes (DEGs), the consistency of DEG category, and suspected false discovery rate (sFDR) were first introduced as statistical indices. In order to validate the availability of these indices, based on the same RNA extract, the analysis was performed by comparing gene expression differences between wild-type and transgenic rice using deep sequencing and microarray. The results suggested that the parameters were available and showed advances in the determination of gene expression differences. Based on relative self-comparison design, suspected false positive genes were easily identified from all DEGs detected, which was difficult for quantitative real-time polymerase chain reaction (qRT-PCR) validation when the count of DEGs was enormous. In addition, sFDRs had advantages in the accuracy evaluation for previous datasets.
Yang
Dong-Yan
DY
Shenzhen Center for Disease Control and Prevention, Shenzhen 518020, P. R. China.
Wang
Xue-Lin
XL
Deng
Ping-Jian
PJ
Zhou
Xiang-Yang
XY
Wu
Xiao-Jin
XJ
Wu
Shui-Qing
SQ
Yang
Xiao-Ke
XK
Hou
Hong-Li
HL
Yang
Yong-Cun
YC
Zhang
Hai-Long
HL
Liu
Jin
J
D020869:Gene Expression Profiling / Q000379:methods*; D018745:Genome, Plant / Q000235:genetics; D006824:Hybridization, Genetic / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012275:Oryza / Q000235:genetics; D020133:Reverse Transcriptase Polymerase Chain Reaction