Since the introduction of mapping quality scores in MAQ (Li et al., 2008) to indicate the probability of the correctness of alignments, the concept of mapping quality scores has been frequently used in many NGS read aligners.
The BWA alignment was used with SAMtools to obtain the InDel locations fast, whereas the trace files from MegAlignTM were used to manually check the correctness of alignments and for manual calling of the variants.
We begin by noting that there is an important trade-off between sensitivity with a specific window size in OPTIMA-Overlap and the correctness of alignments, as can be seen in Fig. 5.
Even in the case of globally optimized alignments by maximum matching approach, correctness of local alignment is not always guaranteed (Brudno et al. 2004).
Generally, a higher mapping quality score indicates a higher confidence in the correctness of an alignment.
The definition of a correctly mapped read introduced in this study is more stringent than for previous studies, because it takes into account the correctness of the alignment (length, number, and type of edit operations).
The biological issue surrounding MSAs is even more complex: given a set of sequences, we do not know how to estimate similarity in a way that will guaranty the biological correctness of an alignment, whether this correctness is defined in evolutionary, structural or functional terms.
To decide the correctness of reported alignments, we use the human rhesus pairwise alignments (rheMac2.hg19.all.chain) provided by UCSC.
VarSim goes further with the ability to validate the correctness of read alignments even near complex SVs.
However, the correctness of the alignments generated by these methods is difficult to assess objectively since little is known about the exact evolutionary history of most proteins.
The knowledge of even one 3D protein structure in a given sequence alignment provides a powerful means to test the correctness of the whole alignment.
