GCphase: an SNP phasing method using a graph partition and error correction algorithm

BMC Bioinformatics

Table 1 Evaluation results based on Nanopore datasets

Sample	Method	Block num	SNP num (%)	SW	SW rate (%)	HMD	HMD rate (%)
Nanopore 50 ×	GCphase	14,593	96.71	262	0.30	6003	7.26
	HapCUT2	14,586	95.70	618	0.70	4087	5.33
	LongPhase	15,454	96.64	450	0.50	6386	8.07
	WhatsHap	15,096	96.01	620	0.71	5061	6.34
Nanopore 30 ×	GCphase	16,690	96.22	352	0.40	8535	9.16
	HapCUT2	16,930	95.46	627	0.69	5984	6.05
	LongPhase	18,031	96.27	569	0.63	10,175	10.55
	WhatsHap	17,661	95.82	639	0.73	5187	5.97
Nanopore 20 ×	GCphase	19,366	95.89	312	0.35	3800	3.20
	HapCUT2	19,456	95.81	740	0.82	3711	4.79
	LongPhase	20,215	95.74	479	0.56	4841	7.47
	WhatsHap	20,095	96.27	661	0.78	3722	4.73

ISSN: 1471-2105