Table 1.
Platform screening potential.
Figure 1.
Relevant figure and table references are noted. Human breast cell lines were cultured and total RNA was extracted. MiRNA profiles were obtained using four different platforms; Exiqon miRCURY LNA, Life Technologies SOLiD4, Illumina HiSeq, and NanoString nCounter. A local miRNA database (Exma-miRDB) was generated based on mature sequences found in miRBase v17. The performances of the platforms were evaluated in regards to accuracy, sensitivity, and flexibility.
Figure 2.
(A) Venn diagram displaying the convergence of detected miRNAs by the four platforms. Dispersion of the concentration of individual miRNAs detected by a single platform (B) and all platforms (C). The miRNAs are grouped in accordance to the percentile distribution, where the 20% lowest expressed miRNAs within a platform are grouped, the miRNAs with an expression between the 20% lowest and the 40% lowest are grouped, and so on.
Table 2.
Platform sensitivity.
Figure 3.
The miRNA fold change values are plotted for every combination of platforms. Fold change values were log2 transformed and Pearson’s correlation (R) was used to assess the accuracy. Confidence limits are included in brackets. Number of miRNA included in the calculation (n). Asterisk (*) indicate p-value <0,0001.
Figure 4.
Platform accuracy in relation to miRNA concentration.
(A) The percent identity in fold change across the percentile distribution of miRNAs for all platform combinations without the nCounter platform. Here, an even accuracy is seen across the full range of miRNA concentration. (B) The same data for platform combinations involving the nCounter platform reveal a large drop in accuracy when the miRNA abundance is low.
Figure 5.
Platform accuracy across fold change level.
Percent identity across the fold change level for every combination of platforms (Paired) and for miRNAs only mutually detected by all platforms (AP).