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. 2018 Sep 11;25(6):619–627. doi: 10.1093/dnares/dsy029

Table 1.

Features used in the ML classification algorithm

Mutation probability A count (low mapq) A prior nucleotide SNV base quality (high mapq)
Read depth (high mapq) C count (low mapq) T PRIOR NUCLEOTIDE SNV base quality (high and low mapq)
Read depth (low mapq) G count (low mapq) C prior nucleotide SNV mapping quality (high mapq)
Unmapped (forward) T count (low mapq) G prior nucleotide SNV mapping quality (high and low mapq)
Unmapped (reverse) A reference A following nucleotide SNV base quality read count (high mapq)
Soft-clipping read depth T reference T following nucleotide SNV mapping quality read count (high mapq)
A count C reference C following nucleotide SNV read count (high and low mapq)
C count G reference G following nucleotide SNV position in read
G count A SNV A and soft-clipping SNV forward strand
T count T SNV C and soft-clipping
Repeat region C SNV G and soft-clipping
Nearby SNV count G SNV T and soft-clipping