Refine Read Mapping

Different sequencing technologies have different advantages and disadvantages and this is also the case when it comes to accuracy. The tool Refine Read Mapping can remove problematic mapped reads with many mismatches in close proximity and mapped reads with an unaligned end of a certain length. Removal of these types of mapped reads can minimize the number of potential false positive variants being reported. Note: The tool considers single end mapped reads. When analyzing paired end mapped reads the tool considers each mapped read in the pair separately.

The tool can be found in the Toolbox here:

        Tools | QIAseq Panel Expert Tools (Image qiaseq_expert_folder_closed_16_n_p) | QIAseq DNA Panel Expert Tools (Image qiaseqv3_folder_open_16_h_p) | Refine Read Mapping (Image remove_marginal_reads_16_n_p)

In the first dialog (figure 6.62), select a read mapping.

Image removemarginalreadsstep1
Figure 6.62: Select a read mapping.

In the second dialog (figure 6.63) the following parameters can be specified:

Image removemarginalreadsstep2
Figure 6.63: Specify the settings for when to remove mapped reads with variants and when to remove mapped reads with unaligned ends.

An example of a read mapping before and after using the Refine Read Mapping is shown in figure 6.64. In this example the mapped reads contain sequencing artifacts that can result in potential false positive calls.

Image nextseqreadmapping
Figure 6.64: A read mapping before (top) and after (bottom) using the tool Refine Read Mapping on the read mapping using default settings for Variants of Window size = 100 and Maximum variants = 6. A false positive variant was reported for one of the G positions before using the tool Refine Read Mapping. The variant is not reported after the mapped reads containing the G artifacts have been removed.

The data used in this example are from a patient sample that were sequenced twice using two different sequencing technologies. Only one sequencing technology had problems with the G pattern shown in figure 6.64.