📄Create a Genomic Sequencing Dashboard (Legacy Platform)
Creating a dashboard to visualize multiple samples with genomic sequencing data
Last updated
Creating a dashboard to visualize multiple samples with genomic sequencing data
Last updated
Prior to working with a series report, ensure that you have set up your library and created a series. VCF files are required to work with the genomic sequencing report.
Select the series you would like to work with and select "Create Series Report". This will open a dialog for you to provide a name, description and select the "BioBox WGS/WES" dashboard.
Go to your workspace and select the "Series Report" tab. Create a new series report- provide a name, description, select a series and the BioBox WGS/WES Dashboard.
Once you create your Series Report create a contrast to compute the variant frequencies to be displayed in the dashboard. Select "Create Contrast", from the top toolbar. Provide a name select "Genomics" as the experiment type and submit the pipeline.
The pipeline progress can be tracked within the Data tab. Once the pipeline is complete you can populate each widget with the data. This should take 1-10 minutes depending on the number of samples in your contrast.
This widget allows you to explore the mutation rate across all genes within your series. By default all mutational consequences identified in your series are selected.
Within the table you can explore:
Gene Symbols
Ensemble IDs
Number of mutations associated with each gene for the selected consequences
The number of samples with more than 1 mutation associated with the selected consequences per gene
The mutational frequency. For each gene this is calculated as
Using " Add Filter" the genes can be further subsetted on the basis of mutational frequency, number of mutations and samples with more than 1 mutation. Once a desired gene list has been achieved, the gene list can be saved. This gene list can be used in the pathway enrichment widget.
This widget allows you to identify the frequency of specific variants across your series and the specific records that were identified to have those variants.
Search for a variant using HGVS nomenclature and you will see the percentage and quantity of this variant across the experiments in your series.
The table will update to display the records associated with experiments where the variant of interest was identified. Selecting the menu icon in the top right hand corner of the table will allow you to customize the metadata properties that are displayed in the table. e.g. if you are interested in the impacts of Cell Type this metadata property can be selected and displayed in the table.
Filtering
Filters can be applied to subset your cohort. Records can be filtered on the basis of any biological metadata that you track. This will reduce the number of experiments that are used in the calculation of variant frequency.
Example.
Let's say you have a Series of 326 experiments and want to see the frequency of variant [NC_000017.11:g.7673753G>C]. The variant frequency is 3.68% as 12/326 experiments within the series are identified to have the variant.
Now you want to see what the variant frequency is amongst patients with a disease diagnosis of Medulloblastoma. Filtering on Disease Diagnosis is Medulloblastoma will reduce the number of experiments identified with the variant.
The variant frequency is 0.92% as 3/326 experiments within the series are identified to have the variant.
The ClinVar Summary Widget enables you to see all ClinVar annotated variants for genes of interest. Note that only genes that have ClinVar annotations will be supported in the widget.
Select a contrast and search for a gene and the table will display all of the ClinVar annotations and clinical metadata. Select the transcripts to view all transcripts associated with each variant.
HGVS identifiers can be copied and used in the variant frequency widget.
The Pathway Enrichment Widget enables you to run an over representation analysis on gene lists that were saved from the Mutational Rate Widget.
Select a bar corresponding to a pathway to see all of the genes enriched in the contrast you have created + filters you have applied. Select a gene to obtain a description of the gene.
Example
Use the mutation rate widget to identify genes that are high frequency mutants, save this gene list and explore the pathways and gene sets enriched across the high frequency mutants.
Search for a specific gene and explore observations across all datasets associated with your series.
Type in a gene and view SNVs on the canonical transcript.
Select “Widgets” from the series report toolbar followed by “Add Widget”. Select “Stacked lollipop from the widget selection menu. This widget will enable you to visualize all of the SNVs associated with a specific gene across all of the samples within the report.
The stacked lollipop widget will appear at the bottom of the report. Select a gene and a genomic sequencing contrast to visualize.
Hover over any of the SNVs to see the metadata
Sample name
Effect
Alt/ Ref
Position
Allele frequency (AF)
Allele count (AC)
Allele number (AN)
Select the cloud icon in the top right hand corner of the plot to export.
To further explore the plot select “Configure plot”
Under series you can swap between genomic tracks and cDNA with the protein domains in addition to filter alleles.
Under Grid you can customize the plot title and subtitle.
Use the drop down above the plot to swap between genes and contrasts.
