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Mapping quality was then assessed across the genome and detected plasmids.
The genome was then broken into 'mapping contigs' where paired-end information was discordance (outside the expected size distribution), mapping quality was high and spanning coverage was low.
Mapping quality was assessed using RSeQC and RNA-SeQC [ 33, 34], which indicated an average read mapping rate of 95.4%% (Additional file 2c), with 92.7 % of reads mapped to intragenic sequences (Additional file 2d) and an average coverage per base of 9.84 reads (Additional file 2e).
Average mapping quality was 30.
The mapping quality was assessed with SAMStat software [ 41].
Read mapping quality was assessed using Samtools v 0.1.19 [ 50].
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Note that although mapping quality is derived in part from base qualities, considering these quantities as independent allows us to encode the fact that base qualities are position specific, while mapping qualities are constant for all bases in the read.
If an alignment algorithm guarantees to find all local alignments, mapping quality is determined by these local alignments only.
Moreover, even for a single mapper, mapping qualities are very data-specific.
In any case where there are two or more equally likely alignments (multiple locations a query can map to), the mapping quality is zero.
For MaxSSmap we consider the read mapped only if mapping quality is above −100 log2.9=15.2.
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