Prediction of sgRNA on-target activity in bacteria by deep learning

BMC Bioinformatics

Table 3 Comparison of Spearman correlation coefficients between eukaryotic sgRNA activity and eukaryotic model predictions

Independent test datasets	Size	DeepCas9	TSAM_U6	CNN_5layers
chari2015Train293T	1234	—	0.3812	0.3607
doench2014HsA375	1276	0.3237	0.3187	0.3369
doench2016	2333	0.3527	0.3439	0.3945
hart2016-GbmAvg	4272	0.3795	0.4242	0.4404
hart2016-Hct1162lib1Avg	4239	0.3679	0.4161	0.4288
hart2016-Hct1162lib2Avg	3617	0.3196	0.3598	0.3829
hart2016-HelaLib1Avg	4256	0.3403	0.3879	0.4033
hart2016-HelaLib2Avg	3845	0.3617	0.3942	0.4390
hart2016-Rpe1Avg	4214	0.2519	0.3094	0.3044
wang2015hg19	2921	0.2030	0.1882	0.2291
xu2015TrainMEsc	981	0.3668	0.4088	0.4111

ISSN: 1471-2105