NanoMod: a computational tool to detect DNA modifications using Nanopore long-read sequencing data

BMC Genomics

Table 1 A summary of simulation data and real data used in the analysis

Datasets	#base in ref ^a	#reads ^b	#modification ^c	Modification types
100 ‘MeanDif’ simulation datasets	6184-bp	200 in each dataset	a group of 60 modifications	Only signal mean of modified bases was affected without neighborhood effect.
100 ‘STDDif’ simulation datasets	6184-bp	200 in each dataset	a group of 60 modifications	Only signal standard deviation of modified bases was affected without neighborhood effect.
100 ‘Mean_STDDif’ simulation datasets	6184-bp	200 in each dataset	a group of 60 modifications	Both signal mean and standard deviation of modified bases were affected without neighborhood effect.
100 ‘Mean_STDDif_NE’ simulation datasets	6184-bp	200 in each dataset	a group of 60 modifications	Both signal mean and standard deviation of modified bases were affected with neighborhood effect.
E. coli [3]	~ 4.64 Mb	181,092	693,586	Methylation at all CpG sites

^aThe number of bases in the reference sequence
^bThe number of reads in a dataset. For simulation data, half of reads have modifications and the other half do not have modifications. For E. Coli, 111,213 reads have methylations and 69,879 do not have methylations
^cThe number of modifications in each dataset

ISSN: 1471-2164