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. 2017 Mar 23;45(11):e103. doi: 10.1093/nar/gkx193

Table 1. NGSCheckMate performance.

Data type Dataset (pair type) Sequencing depth1 Individual Sample Test pairs #matched, #unmatched Accuracy (%)2
WGS (BAM) TCGA colorectal (cancer versus normal) >30X, down-sampling (0.5–30X) 66 132 66, 66 100
down-sampling (0.01–0.2X) 55.3–99.2
WGS (BAM, FASTQ) non-TCGA lymphoma (cancer versus normal) 30–60X, down-sampling (0.5–30X) 14 28 14, 28 100, 100
WES (BAM) TCGA 9 cancer types (cancer versus normal) ∼100X 421 842 421, 421 100
TCGA kidney (cancer versus normal) ∼100X, down-sampling (0.5–30X) 50 100 50, 50 100
WES (FASTQ) non-TCGA breast (cancer versus normal) ∼60X, down-sampling (0.5–10X) 68 136 68, 68 100
RNA-seq (BAM) TCGA colorectal (cancer versus normal) ∼65X, down-sampling (0.5–10X) 19 38 19, 19 100
Single-cell WGS (BAM) single-neuron ∼42X, down-sampling (0.5–10X) 3 36 210, 210 100
glioblastoma (cancer–cancer) 0.01–0.3X 2 89 45, 45 87.8
Chip-seq (BAM, FASTQ) within marks 5.4 (2.2–19.0) 8 119 72, 72 97.6, 97.7
input versus mark input DNA 2.3 (2.1–2.9) 8 127 133, 133 98.5, 99.8
Panel-seq (BAM, FASTQ) cancer versus normal, multiple regions, primary versus metastasis 40 (20–119) 5, 18, 11 12, 48, 25 92, 87 98.3, 99.4
RNA-seq versus WES (BAM) TCGA stomach (cancer or normal DNA versus cancer RNA) RNA-seq (∼70X) WES (∼100X) 65 201 132,132 100
RNA-seq versus WES (FASTQ) non-TCGA breast cancer (cancer or normal DNA versus cancer RNA) RNA-seq (∼25X) WES (∼60X), down-sampling for both datasets (0.5–10X) 53 159 106, 106 100
RNA- versus ChIP-seq (BAM, FASTQ) RNA-seq versus ChIP-seq (all marks) RNA-seq (∼5X) ChIP-seq (described above) 7 119 231, 231 99, 98.9

1For WGS, WES and RNA-seq, the average mean depth is shown. For Panel-seq and ChIP-seq, the average of the mean non-zero depths across the SNPs with at least one mapped read is shown with its range in parentheses.

2Accuracy estimates for the alignment-based and the alignment-free method are separated by a comma.