Fig. 2: Wet-lab proficiency in omics data generation varies. | Nature Biotechnology

Fig. 2: Wet-lab proficiency in omics data generation varies.

From: Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials

Fig. 2: Wet-lab proficiency in omics data generation varies.

a, The number of features detected from each dataset generated in different labs using different platforms. b, Distribution of the number of experiments supporting genomic variant calling or CV in quantitative omics profiling from technical replicates (analytical repeats in SV calling and library repeats for the others) within a batch. c, Technical reproducibility from three replicates within a batch, calculated as the Jaccard index for small variant calling and Pearson correlation coefficient (r) for quantitative omics profiling (n = 12). For SV call sets, technical reproducibility was defined as the Jaccard index between different analytical repeats (Oxford Nanopore, n = 28; PacBio Sequal, n = 55; PacBio Sequal2, n = 55). The box plots display the distribution of data, with the median represented by the line inside the box and the interquartile range represented by the box. Whiskers extend to 1.5× the interquartile range. d, SNR based on the Quartet multi-sample design (4 samples × 3 replicates per batch). e, RMSE of high-confidence DEFs. Dots represent RMSE values for the D5–F7, D5–M8 and F7–M8 pairs in each batch (n = 3), while the bar plots present the corresponding mean values.

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