Optimized pipeline of MuTect and GATK tools to improve the detection of somatic single nucleotide polymorphisms in whole-exome sequencing data

Table 4 The GATK-LOD_N method presented good performance in artificial tumor samples. Performance of MuTect and GATK-LOD_N for artificial tumor samples that had variants with diverse allelic frequencies

		Artificial Tumor Samples
		Low Frequency Variants (n = 22) VAF: 0.02 – 0.26	Intermediate Frequency Variants (n = 25) VAF: 0.5 – 0.86	High Frequency Variants (n = 25) VAF: 0.97 – 1
MuTect	Somatic Candidates	22	25	25
	TP	19	25	25
	FN	0	0	0
	FP	3	0	0
	PPV	19/22	25/25	25/25
	FDR	3/22	0/25	0/25
GATK-LOD_N	Somatic Candidates	27	32	33
	TP	17	23	23
	FN	5	5	2
	FP	5	7	8
	PPV	17/22	23/30	23/31
	FDR	5/22	7/30	8/31

TP True positives, FN False negatives, FP False positives, PPV Positive Predictive Value (#TP / #FP + #TP), FDR False Discovery Rate (#FP / #FP + #TP), VAF Variant Allelic Frequency
GATK results were not reported in the table since it detected more than 2200 candidates out of 22 or 25 TPs

ISSN: 1471-2105