This post explains how to perform genetic variant annotation for a given set of SNPs. This feature is powered by the snpEff software; you can find the original research paper here: https://www.tandfonline.com/doi/full/10.4161/fly.19695.
The genetic variant annotation features are available in QTLmax Super and require the following two steps:
- SNP extraction (QTLmax Super > SNP extraction)
- snpEff tool (QTLmax Super > snpEff tool)
Figure 1 shows the tab page called “(1) SNP extraction” for the first step, in which you are required to enter a list of SNP names to extract from a given input file in a VCF or VCF.GZ format. In real practice, your list of SNPs would be made up of QTL markers resulting from GWAS. The resulting output will be displayed in the output box. Please note that its resulting file will be used in the next step.
(Figure 1)
Figure 2 shows the tab page called ‘(2) snpEff tool’ for the second step of SNP annotation. As mentioned above, this feature uses the output from the first procedure as input.
Next, you must select a genome DB for your species. To do this, follow these steps:
- Select the appropriate genus from the ‘Genus name’ list box and press the [Select] button; this will populate the ‘Species epithet’ list box.
- Select the appropriate species from the ‘Species epithet’ list box and press the [Download] button; this will populate the ‘Selected Sequence Data’ list box.
- Select the item that matches your target species from the ‘Selected Sequence Data’ list box.
It is important to note that the downloaded ‘Species epithet’ DB file is saved in the following directory:
~/Documents/snpEff.DB
If the ‘snpEff.DB’ directory does not exists, it will be automatically created. The existing DB files can be navigated within the file tree box under the tab page labeled “Reference genome directory” as shown in Figure 2.
(Figure 2)
The current demo dataset in this example addresses Oryza sativa, a cultivated rice species; accordingly, Figure 3 presents the Oryza sativa DB being selected and its annotation output being returned.
(Figure 3)
Figure 4 shows the summary of genetic variants, which is another output returned from the same input dataset.
(Figure 4)