Fig. 3

BRB-seq’s overall performance relative to TruSeq. a Correlation of log2 read counts between technical replicates at t14 for the BRB-seq workflow (Pearson correlation r = 0.987). b Correlation of log2 read counts between BRB-seq and TruSeq (Pearson correlation r = 0.920). c Comparison of read alignment performances between BRB-seq and TruSeq. The no/multiple alignment values are derived from the STAR [35] alignment, and no gene/ambiguous and mapped to genes correspond to the annotation of the reads to the genes by Htseq [49]. d Comparison of library complexity between BRB-seq and TruSeq (e.g., “Reads > 0” means that a gene is considered detected if it is covered by at least one read). e Evaluation of BRB-seq’s performance relative to TruSeq using the data downsampled to 1M single-end reads and shown by the total number of identified DE genes and the number of “true positive” DE genes. The latter represents a subset of DE genes identified using the full TruSeq 30M paired-end set (see the “Methods” section). f The distribution of RPKM levels of expression of the DE genes detected (blue) or not detected (red) in the downsampled TruSeq (dotted) or BRB-seq (plain) that overlaps with the “gold standard” TruSeq ~ 30M paired-end reads. g The sequencing depth required for detecting genes with a given CPM expression level using TruSeq and BRB-seq libraries. A sequencing depth is considered sufficient if the gene is detected more than 95% of the time. h Power simulation analysis of public and in-house bulk SCRB-seq, BRB-seq, and TruSeq datasets (*p < 0.001; n.s. non-significant). i Correlation of expression values (normalized to HPRT1) determined by qPCR (in replicates, with 50 ng and 500 ng of total RNA used per RT), TruSeq and BRB-seq. Pearson’s r values are indicated. In all panels, for an unbiased comparison, all libraries were randomly downsampled to one million single-end reads (see the “Methods” section)