Effect of high variation in transcript expression on identifying differentially expressed genes in RNA‐seq analysis

Abstract

Summary Great efforts have been made on the algorithms that deal with RNA‐seq data to enhance the accuracy and efficiency of differential expression (DE) analysis. However, no consensus has been reached on the proper threshold values of fold change and adjusted p‐value for filtering differentially expressed genes (DEGs). It is generally believed that the more stringent the filtering threshold, the more reliable the result of a DE analysis. Nevertheless, by analyzing the impact of both adjusted p‐value and fold change thresholds on DE analyses, with RNA‐seq data obtained for three different cancer types from the Cancer Genome Atlas (TCGA) database, we found that, for a given sample size, the reproducibility of DE results became poorer when more stringent thresholds were applied. No matter which threshold level was applied, the overlap rates of DEGs were generally lower for small sample sizes than for large sample sizes. The raw read count analysis demonstrated that the transcript expression of the same gene in different samples, whether in tumor groups or in normal groups, showed high variations, which resulted in a drastic fluctuation in fold change values and adjustedp‐values when different sets of samples were used. Overall, more stringent thresholds did not yield more reliable DEGs due to high variations in transcript expression; the reliability of DEGs obtained with small sample sizes was more susceptible to these variations. Therefore, less stringent thresholds are recommended for screening DEGs. Moreover, large sample sizes should be considered in RNA‐seq experimental designs to reduce the interfering effect of variations in transcript expression on DEG identification.

The involvement of collagen family genes in tumor enlargement of gastric cancer

“…Similarly, e dgeR analysis revealed that COL11A2 was significantly down-regulated in T2, T3, and T4 stages, but the difference was not significant in Wilcoxon tests. By examining the read count values of COL2A1 and COL11A2, the large fold change values obtained using edgeR were caused by a few extreme outlier expression values, which was consistent with previous studies 23 , 24 .…”

“…As a landmark cancer genomics program, TCGA sequenced and molecularly characterized a great many cases of various kinds of primary cancer samples. Due to the high variation in mRNA expression, differentially expressed genes (DEGs) identified using a larger sample size are more reliable in RNA-Seq analysis 23 , 24 . The number of GC samples in TCGA is much larger than that in any single study in other databases, and RNA-Seq is more accurate than the microarray technology; however, the expression patterns of collagen family genes in GC samples in TCGA has not been systematically explored.…”

Transcriptomic and proteomic retinal pigment epithelium signatures of age-related macular degeneration

“… 60 ; according to a study in ref. 61 , studies with smaller sample sizes had greater variation in the number of transcripts quantified for each gene.…”

NETest: serial liquid biopsies in gastroenteropancreatic NET surveillance

“…Inter-tumoral and intra-tumoral heterogeneity is recognized in many solid tumors, creating obstacles in the identification and development of new biomarkers (28,29). A recent paper by Childs et al demonstrated significant intra-and inter patient genomic heterogeneity in circulating tumor cells (CTC) from NETs (29).…”

“…The tumor micro-environment is a complex ecosystem in which cancer cells interact with a diverse range of immune, stromal and endothelial cells, constantly shaping and changing the molecular biology of a tumor ( 27 ). Inter-tumoral and intra-tumoral heterogeneity is recognized in many solid tumors, creating obstacles in the identification and development of new biomarkers ( 28 , 29 ). A recent paper by Childs and coworkers demonstrated significant intra- and inter-patient genomic heterogeneity in circulating tumor cells from NETs ( 29 ).…”