A number of realignment or assembly methods have been proposed to overcome the alignment errors and reference bias that limit indel detection.
Therefore, either SNP calling algorithms need to be indel-'aware' or potential indels should first be identified, local realignment or assembly performed around them, followed by SNP calling after completion of these initial steps.
Iterations of assembly, realignment and editing using BWA, MUMmer and Gap5 were performed to complete the genome assembly.
The developed three-station quality management model has the potential to decrease the overall cost of a project by reducing the fabrication rework required as well as by avoiding costly and time-consuming site assembly realignments, which are often caused by defects in the fabrication and delivery processes.
To our knowledge, ScanIndel is the only method that has been specifically developed to perform both soft-clipping realignment and de novo assembly for indel detection.
Overall, when combining both soft-clipping realignment and de novo assembly approaches, we achieved the highest sensitivity for both insertions and deletions across the full spectrum of simulated indel sizes.
Realignment of the genome assemblies was then performed to visualize the optimization and final architecture of the draft genomes.
Multiple sources of error exist, including incomplete or incorrect reference assemblies, erroneous realignment of reads to the reference genome (particularly in low complexity regions and around indels), inaccurate base quality scores, and suboptimal variant filtration parameters (Depristo et al. 2011; Li 2014).
Results: We present ABRA, an assembly-based realigner, which uses an efficient and flexible localized de novo assembly followed by global realignment to more accurately remap reads.
Therefore, ScanIndel was called with soft-clipping realignment only mode, which disabled the assembly step.
