MONTAGE: a new tool for high-throughput detection of mosaic copy number variation

BMC Genomics

Table 1 Performance Comparison of Mosaic CNV Detection Tools

Algorithm	Install	Runtime	Sensitivity	Specificity	URL
MONTAGE	Easy	Short (35 s/10s^a)	Good(1/1)	Good(0/0)	https://github.com/CAG-CNV/MONTAGE
MoChA	Difficult	Long (1m1s^b)	Good(1/1)	Good(0/0)	https://github.com/freeseek/mocha
RGADA-MAD	Difficult	Short (14 s)	Low(0/1)	Low(1/0)	https://github.com/isglobal-brge/MAD
BAFSegmentation	Easy	Long (1m14s)	Good(1/1)	Low(186/0)	http://baseplugins.thep.lu.se/wiki/se.lu.onk. BAFsegmentation
triPOD	Easy	Very Long (10 m)	Low(0/1)	Low(0/0)	https://github.com/jdbaugher/tripod

Install ease based on actual setup with non-superuser credentials, not exclusively the documented setup instructions provided by the algorithm. Runtime listed per sample 610 k density SNP microarray. ^aSorted by chromosome and position input file. ^bEagle phasing pipeline (1 m) and Chromosomal alterations pipeline (1 s) steps included. Sensitivity and Specificity based on running the same sample data through each algorithm and comparing results. In parenthesis is Observed / Expected mosaic CNV calls. See Fig. 7 for additional Sensitivity/Specificity analysis where we demonstrate in 755 samples a 0.975 false positive rate 0.344 (MONTAGE) vs. sensitivity of 0.920 at false positive rate 0.598 (MoCha) vs. sensitivity of 0.280 at false positive rate 0.627 (RGADA-MAD)

ISSN: 1471-2164