AirVariant

This plugin allows users to upload genomic variant data files to find and predict the effects of mutations on elements in the AIR. Results can then be used in the -omics plugin to estimate their effect on processes and phenotypes.

Guide:

1. Upload gene variant file(s)

The user selects one or multiple local .vcf files by clicking on (1). Currently, we include the human genomes releases Hg19 and hg38 that can be selected in (2). Furthermore, the user can select in (3) whether negative-strand transcripts should be considered in the analysis. After clicking on (4), all uploaded variants for each sample will be tried to mapped on transcripts of all elements in the AIR, and the results are displayed in table (5). The table contains in each row a checkbox to select the specific gene for further predictions, the gene name, chromosome, number of transcripts (that can be filtered for). and the number of unique variants in each sample.

 

2. Predict variant effects

To analyze the consequences of variants we use the Ensembl Variant Effect Predictor (VEP) API. In (7), genes, for which the effects of the mutations should be predicted, can be selected by typing their official gene names separated by a comma. For facilitation, with the buttons at (6), all genes visible in the submaps on MINERVA can be added at once, or all already selected genes be reset. (8) allows filtering common variants by their frequency in the populations as provided by the Genome Aggregation Database (gnomAD). Clicking on (9) then sends all variants to ensembl for prediction and display results as mutation impacts for each sample in the table below. This operation will take quite some time (approx. 5 variants per second), however, already fetched variants are stored in memory. This way variants that may exist in multiple samples will only be fetched once and changing the frequency threshold will not result in a new request. The table can be reset by clicking on (10). Results can be downloaded as a .txt file (11).

 

 

3. Visualize mutations as overlays in MINERVA

The results of the previous table can also be displayed as overlays on the specific genes on the map itself, however, the user has to be logged in to do so. Mutation impacts will be color-coded with Red = High, Medium = Yellow, Modifier = Grey and Low = Green. Furthermore, the number of transcripts or the number of variants for each gene can be visualized (color-coded as a gradient from white to red) (12). The user has to specify a name for the overlay in (13) which will then be extended by "_{samplename}" for each sample. Clicking on (14) creates the overlays that then can be selected or edited in the MINERVA overlay panel on the left.