Figure 1.
For each read (paired-end specifically, single-end is only with step 1 and step 3), the alignment would be decided in at most three steps. In step 1, SOAP3-dp aligns both ends of a read-pair to the reference genome by using GPU version 2way-BWT algorithm (Methods). Pairs with only one end aligned proceed to step 2 for a GPU accelerated dynamic programming (Methods) alignment at candidate regions inferred from the aligned end. Pairs with both ends unaligned in step 1 and those ends failed in step 2 proceed to step 3 to perform a more comprehensive alignment across the whole genome until all seed hits (substrings from the read) are examined or until a sufficient number of alignments are examined.
Table 1.
Benchmarking using real reads.
Figure 2.
Speed and sensitivity of alignment using simulated paired-end reads.
We recorded the number of correct and incorrect alignments stratified by reported mapping quality for each dataset. We then calculated the cumulative number of correct and incorrect alignments from high to low mapping quality. We considered an alignment correct only if the leftmost position was within 50 bp of the position assigned by the simulator on the same strand according to the previous study of Bowtie2 to avoid soft-clipping artifacts.
Table 2.
Comparison on 16 sets of programs and parameters using 100 bp paired-end simulated reads.
Figure 3.
The accumulated number of incorrectly aligned reads categorized at different mapping quality scores by the five aligners.
Figure 4.
Alignment time consumption of using GPU card “GTX680” and previous generation GPU card “Tesla C2070” respectively.
Table 3.
Summary of alignment and variation calling using SOAP3-dp and BWA with different parameters and datasets.
Figure 5.
The length distribution of Indels identified by SOAP3-dp and BWA respectively using full set of 100 bp paired-end YH sample reads.
a. Indels smaller than or equal to 20 bp, b. larger than 20 bp.