Table 1.

Read alignment and Data visualization Tools.

S.No	Tools	Advantages	Disadvantages	References
1	BatMeth2	Indel-sensitive mapping	Removes some parts of reads (soft-clipping)	[129]
2	BSMAP	Good performance and flexibility due to seeding and hashing	Can detect indels with length less than 3 nucleotides only	[130]
3	Bismark	Flexible, easy to use and interpret	Increased run time	[131]
4	BS-Seeker2	Supports both local and gapped alignments	Local alignment leads to longer CPU times	[132]
5	BWA-meth	Direct useable output, less storage requirements	doesn’t facilitate data visualization, only supports 3-letter alignment mode	[133]
6	BSmooth	Ability to handle low coverage experimental data	Assumes methylation profiles to be smooth, not able to detect single CpG sites	[134]
7	MethylCoder	Allows fast and sensitive mapping in both color and nucleotide space	Uses only short read aligners	[135]
8	Segemehl	Efficiently handles 3’ and 5’ contaminants along with mismatches and indels	Large memory requirements	[136]
9	GSNAP	SNP tolerant alignment, splicing and multiple mismatches can be detected	Might be slow for long positions	[137]
10	BRAT-BW	Runs faster on longer reads	Allows at most one mismatch in user defined reads	[138]
11	ERNE-BS5	Analysis of methylation pattern at repeats, skillfully handles multiple mapping reads	Chances of false positives are higher	[139]
12	GEM3	Exhaustive search model, fast, scalable, and gapped matches can also be found	some pruning methods are sensitive to mismatches	[140]
13	Last	High sensitivity and speed	Requires removal of poor quality bases	[141]
14	Msuite	supports bisulfite-free techniques,4-letter mode of alignment and computationally less expensive	analysis on irregular CpG sites needs additional validation	[142]
15	TAMeBS	Filters ambiguous read alignments and reduces bias in context of methylated cytosines	Memory requirements and running time are high	[143]