Fig. 2 | Nature Communications

Fig. 2

From: CUTseq is a versatile method for preparing multiplexed DNA sequencing libraries from low-input samples

Fig. 2

CUTseq validation. a Copy number profiles (NlaIII, 100 kb resolution) determined with CUTseq and NEBNext using gDNA extracted from ten different FPPE tumors. BRCA, breast cancer. COAD, colon adenocarcinoma. GIST, gastrointestinal stromal tumor. MELA, melanoma. ρ, Pearson’s correlation between matched profiles. b Pearson’s correlation (ρ) between the fraction of the genome (100 kb resolution) either amplified or deleted in each of the paired CUTseq and NEBNext samples shown in a. Each dot represents one pair of replicates. Dashed line: linear regression. c Partitioning of all the SNVs called in two replicate (Rep) exome capture experiments using SKBR3 cells gDNA and either CUTseq or a commercial kit for library preparation (Agilent), in multiple different annotated genomic regions. Up- and downstream indicate 5 kb windows before the start codons and after the stop codons of protein-coding genes, respectively. d Same as in c, but for different substitution types. e Overlap between the high-confidence SNVs (at least 50× coverage) called in the two CUTseq replicates shown in c, d. f Overlap between all the high-confidence SNVs identified by CUTseq vs. Agilent, after merging matched replicates shown in c, d. In both e and f, the percentages refer to the total number of SNVs in the union of the two sets. All the source data for this figure are provided as a Source Data file

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