In this example let's look at an artificially added variant to a simulated raw signal.
We simulated two sets of reads from two reference genomes. The only difference between the two genomes is a single SNV at 346th base.
One has T; the other has A.
The pipeline data is at test/data/raw/pipelines/pipeline_1/simulated_variant.
Note that the script must be executed inside the virtual environment where squigualiser is installed.
The following variables must be changed before running the bash script.
| Variable name | Description | value set for this pipeline |
|---|---|---|
| SQUIGULATOR | path to squigulator | - |
| SAMTOOLS | path to samtools | - |
| SLOW5TOOLS | path to slow5tools | - |
| SIMULATING_PROFILE | signal profile used by squigulator (-x argument) | dna-r10-prom |
| PROFILE_TO_DETERMINE_BASE_SHIFT | squigualiser uses this value to determine the appropriate base_shift. More details can be found at profiles |
kmer_model_dna_r10.4.1_e8.2_400bps_9_mer |
| SIM_REGION | (optional) The region to plot in simulated read and the reference. | sim_ref:300-500 |
In the bash script run.sh two signal files are simulated one for each genome. Then the two signal files and the alignment SAM files are merged separately before generating a pileup.
Fig. 1 shows the pileup of the forward mapped reads. At base index 46, the second and the seventh read have T and the rest have A. This can be easily seen in the overlap plot at the top.
Fig. 2 shows the pileup of the reverse mapped reads. However, it is not very noticeable as in the forward pileup.
Figure 1
Figure 2