Fig. 4

Quantitative comparison among Quartz-Seq2 and previously reported methods using embryonic stem cells. a We determined the UMI and gene counts with Quartz-Seq2 in the RT25 condition using J1 ES cells. We performed Quartz-Seq2 (RT25) with three sets of 384-well plates and two sets of 384-well plates on different days. We also estimated the UMI conversion efficiency of other single-cell RNA-seq methods (CEL-seq2(C1), SCRB-seq, MARS-seq, and Drop-seq) from a previous study that used mouse ES cells [21]. In our comparison, the Read2 length for transcript mapping was 45 nucleotides for all of the methods, including Quartz-Seq2. We estimated the average UMI and gene counts and the UMI conversion efficiency with various numbers of initial fastq reads for each method. The findings indicate that, compared with the other methods, Quartz-Seq2 has a superior ability to detect UMI and gene counts from limited initial amounts of data (under 0.2 million fastq reads). b To investigate the throughput capacity for establishing sequence library DNA, we estimated the number of processable single cells per $1000 spent on each method: Quartz-Seq2 (384 indexes, RT25) yielded 1785 cells, Quartz-Seq2 (384 indexes, RT6.25) yielded 2325 cells, Quartz-Seq2 (384 indexes, RT6.25 + column1) yielded 3058 cells, Quartz-Seq2 (1536 indexes, RT25) yielded 2500 cells, CEL-seq2(C1) yielded 111 cells, SCRB-seq yielded 500 cells, MARS-seq yielded 769 cells, and Drop-seq yielded 10,000 cells. The UMI conversion efficiency was approximately 32.55% (n = 1152), 32.25% (n = 768), and 32.12% (n = 192) for Quartz-Seq2 (384 indexes, RT25), 35.48% (n = 2304) for Quartz-Seq2 (1536 indexes, RT25), 34.04% (n = 768) for Quartz-Seq2 (384 indexes, RT6.25), 35.51% (n = 768) for Quartz-Seq2 (384 indexes, RT6.25 + column1), 22.4% for CEL-seq2(C1), 13.3% for SCRB-seq, 10.6% for MARS-seq, and 7.1% for Drop-seq. The average gene count was approximately 6636 (n = 1152), 6584 (n = 768), and 6529 (n = 192) for Quartz-Seq2 (384 indexes, RT25), 6712 (n = 2304) for Quartz-Seq2 (1536 indexes, RT25), 6753 (n = 768) for Quartz-Seq2 (384 indexes, RT6.25), 6794 (n = 768) for Quartz-Seq2 (384 indexes, RT6.25 + column1), 5164 for CEL-seq2(C1), 4044 for SCRB-seq, 3252 for MARS-seq, and 2738 for Drop-seq