MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads

BMC Bioinformatics

Table 12 Alignment statistics for various benchmarking error detection and correction tools

Tools	S. aureus		H. Chr14		Arabidopsis thaliana Chr1		Metriaclima zebra
Tools	Mapped reads*	Alignment rate (%)	Mapped reads*	Alignment rate (%)	Mapped reads*	Alignment rate (%)	Mapped reads*	Alignment rate (%)
Lighter	565,623	33.82	992,819	99.28	272,145	90.72	742,408	82.49
BFC	562,978	33.66	989,326	98.93	272,221	90.74	741,331	82.37
RECKONER	555,322	33.20	989,606	98.96	275,333	91.78	754,974	83.67
Fiona	548,248	32.78	957,850	95.78	265,828	88.61	722,217	80.59
Karect	588,395	35.18	991,623	99.16	275,393	91.80	753,414	83.71
Pollux	441,739	36.77	312,731	99.15	128,813	92.62	297,605	91.23
CARE**	541,616	32.38	990,305	99.03	272,150	90.72	744,147	82.68
MAC-ErrorReads***	540,246	38.69	959,644	99.14	262,880	90.87	699,018	83.76

*Bowtie 2 is utilized to generate these statistics, wherein the total number of mapped reads encompasses those aligned only once as well as those aligned multiple times
**CARE relies on RF machine learning model for error correction
***MAC-ErrorReads is a filtration tool that classifies reads as either correct or erroneous but does not perform error correction for the reads classified as erroneous

ISSN: 1471-2105