Output from the Identify QIAseq DNA Variants workflow
The Identify QIAseq DNA Variants workflow produces a Genome Browser View () as well as the following files, available in a subfolder as seen in figure 3.6):
- a Trim Reads Report () where you can check that adapters which adapters were detected by the automatic detection option
- a UMI Groups Report () containing a breakdown of UMI groups with different number of reads, along with percentage of groups and reads
- a Create UMI Report () that indicates how many reads were ignored and the reason why they were not included in a UMI read.
- a read mapping of the UMI Reads ()
- a coverage report and a coverage track from the QC for Target Sequencing tool (see http://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=QC_Targeted_Sequencing.html)
- two variant tracks: the Unfiltered Variants is output before the filtering steps, the Variants passing filters is the one used in the Genome Browser View (see http://resources.qiagenbioinformatics.com/manuals/clcgenomicsworkbench/current/index.php?manual=_annotated_variant_table.html for a definition of the variant table content).
- one amino acid track
- when a read mapping was submitted in the Copy Number Variant Detection dialog, the workflow also ouptputs three CNV tracks (Target-, Region- and Gene-level) and a CNV Results report.
Figure 3.6: Output from the Identify QIAseq DNA Variants workflow without CNV detection.
The Unfiltered variants track is included in the output so you can also review why a variant that was expected in the output would have been filtered out of the Variants passing filters track. The difference between the Unfiltered variants track and the Variants passing filters track depends on the following options available in the filtering steps:
- Filter based on quality criteria: Average Quality (quality of the sequenced bases that carry the variant), QUAL (significance of the variant), Read Position Test Probability (relative location of the variant in the reads that cover the variant position) and Read Direction Test Probability (relative presence of the variant in the reads from different directions that cover the variant position).
- Remove homopolymer error type variants, i.e., errors of the indel type that occur in homopolymer regions. These regions are known to be harder to sequence than non-homopolymeric regions. Note that the definition of homopolymere regions differs between the pipelines due to differences in sequencing technology.
- Remove false positive based on frequency: the variant's frequency needs to be above that threshold for the variant to be output by the workflow in the filtered variant track. Note that because the unfiltered variant track is produced by the Low Frequency Variant Detection tool run with a frequency cut-off value of 0.5, it does not make sense to filter the variants with a value lower than 0.5. In fact, we recommend filtering with a value that is at least twice the frequency cut-off value of 0.5.
The workflow also produces a QC report for the target enrichment that offers statistics on the numbers of targets for which all positions are covered by the "Minimum coverage" threshold set in the QC for targeted sequencing dialog.
The read mapping of the merged UMI groups will let you verify the found variants, and examine why expected variants were not found. The UMI Groups Report gives information about the number of UMI groups found, and how many reads are in each. It includes the following information:
- How many reads were aligned to the reference (Reads in input).
- How many reads were mapped in multiple places and thus discarded.
- Groups merged: How many groups were created by merging singleton groups with other groups.
- Number of groups that were discarded for being too small (by default 0 but the option "Minimum group size" of the Calculate Unique Molecular Index Groups can be set up to discard small groups), and how many reads were thus discarded.
- How many groups were created, and of these how many were singletons groups (groups made with sequences sharing identical UMI).
- How many reads are in the largest group.
- How many different UMIs are in the most divergent group (different sequences with different UMIs can be in the same group, if they start on the same position and if they have UMIs that only differ with one character).
- Statistics about the number of reads in the groups.
- Statistics about groups size and reads not included in these groups (also available as graphs below the table).
Note about exporting output files in SAM/BAM format Exporting UMI reads as BAM files will show UMI described as Unique_Molecular_Index=[number1]_count=[number2], where number1 is a UMI ID (just a unique UMI group number), and number2 is the number of reads that are in that UMI group.