Table 1.

Comparison of recall rates (RR) of different NGS-based miRNA identification tools using various data sets

Organism and	Identification	miRNA reference data		N recall	RR	N tot	SPC
library reference	method	Source	N ref
Chlamydomonas reinhardtii
Simulated	miRA	Molnar et al. [8]	20	12	0.60	19	1.0
Simulated	miR-PREFeR	Molnar et al. [8]	20	0	0.00	0	1.0
Loizeau et al. [36]	miRA	Molnar et al. [8]	47	39	0.83	281	–
Loizeau et al. [36]	miRDP	Molnar et al. [8]	47	14	0.30	964	–
Loizeau et al. [36]	miR-PREFeR	Molnar et al. [8]	47	29	0.62	60	–
Molnar et al. [8]	miRA	Molnar et al. [8]	15	12	0.80	175	–
Molnar et al. [8]	miRDP	Molnar et al. [8]	15	7	0.47	51	–
Molnar et al. [8]	miR-PREFeR	Molnar et al. [8]	15	3	0.20	6	–
Arabidopsis thaliana
Pooled Athl-2 [28]	miRA	miRBase	246	122	0.50	517	–
Pooled Athl-2 [28]	miRDP	miRBase	246	80	0.12	695	–
Pooled Athl-2 [28]	miR-PREFeR	miRBase	246	119	0.48	138	–
Volvox carteri
Novel data	miRA	–	0	–	–	213	–

We compare the performance of miRA, miRDP [29], and miR-PREFeR [28] using simulated and experimental algae NGS data (Chlamydomonas reinhardtii and Volvox carteri), and Arabidopsis thaliana NGS data. Details of the simulated data are given in the text. We determine the number of reference miRNAs for each library by requiring a minimum expression of 10 reads for each known reference miRNA. The source and number N _ref of known miRNAs for the different organisms are given in columns 3 and 4. N _recall gives the number of identified known miRNAs. N _tot gives the total number of identified miRNAs. For the simulated data we provide the specificity (SPC) in the last column