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The advantages of using many alignments as input to OQC becomes more apparent in our test of SV breakpoint detection in the next section.
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Using the CQ method, a sequence is classified as Y-linked if it has more than 3.33 times as many alignments from male data than from female data, and therefore a CQ less than 0.3.
For example, human (Homo sapiens), being the most complete, has the largest number of alignments of the other vertebrate species, followed by pig (Sus scrofa), and while bison (Bison bison bison) and water buffalo (Bubalus bubalis) are more closely related to cattle than human or pig, these bovids have less sequence data available and thus do not produce as many alignments.
For a sequence to be classified as Y-linked with the chromosome quotient it must have many alignments from males, and zero or a few alignments from females.
We used the -a option to retain as many good alignments as possible for each read.
Since the alignment process is computationally intensive, many alignment tools are designed as parallel applications, typically targeting multicore platforms.
Many alignment algorithms exist.
For many alignment methods, rescoring of alignment-induced models using structural information can improve the separation of useful and less useful models as compared with the alignment score.
There are many alignment formats available.
Many alignment methods often produce reasonable alignments which score worse than alignments with alternative templates.
These prove to be effective settings, as Y4 produces ~1.6× as many GE50U alignments per CPU second as the other YAHA runs, and ~2.5× as many as M. Given these results, we use 650 as the maxHits threshold for YAHA in the accuracy test below.
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