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Overview

The Omics Explorer allows users to view a subject’s genetic test data along with annotations from external germline and somatic variant databases in an easy to navigate format.

The video below shows a quick video of the various features of the Omics Explorer.

How to Access the Omics Explorer

To access the Omics Explorer:

  1. Navigate to the Subjects tab on the left of the PHC screen
  2. Locate the subject in the Subjects Table whose data you wish to view by:
    • Selecting NO filters, which allows you to scroll through the list of all subjects in your project.
    • Using filters to locate your subject.
  3. Launch Omics Explorer by:

    • Hovering over the subject's row to access the Omics Explorer button . Click to launch it.

    Launch button

    OR

    • Clicking on the subject (which launches Subject Viewer), then clicking the Omics Explorer icon in the top right-hand corner of the screen

    Launch button 2


Omics Explorer Layout

The Omics Explorer is laid out with a banner with patient and test/sample info atop the page, a data table, and a column of filters on the left.

The blue banner at the top of the Omics Explorer includes the following information:

Header

  • Project Name/Subject Name: Clicking the masked mode icon to unmasked mode in the top right hand corner of the page will change what info is displayed (see clip below).

    Omics Masked

  • Basic demographics about the subject (living status, race, ethnicity, DOB, and age)

  • Genetic tests dropdown menu (test data from genetic testing vendors are grouped as a “test”): The most recent test is sorted to the top of the dropdown. Genetic test info includes:

    • Sequence Name (test) such as Ashion
    • Sequence Type (refers to the type of test)
    • Date
  • Body Site: Where tissue sample came from (breast biopsy, saliva, blood, and so on)

  • Tumor Site of Prediction: This prediction uses RNA-seq data to map it to TCGA tumor types to predict where in the body the tumor came from. As data enters the PHC (such as from Ashion), this prediction is initiated as part of the workflow. It's performed using external resources, such as CancerScope1, and a tool created by LifeOmic (PCANN).

    Tumor Prediction

    Clicking on the TumorSite Prediction abbreviations in the header will give you a more detailed view (see image above):

    • Where the prediction came from (PCANN = a LifeOmic tool, or CancerScope1 = an external tool)
    • What site the tumor is predicted to originate from
    • The confidence score of that prediction (zero = least confident, one = most confident)

    This is useful especially when the site of origin is unknown, or if it's liver cancer this can help determine if it's liver cancer or breast cancer that metastasized to the liver.

  • MSI: Microsatellite Instability: This tells how genomically stable the cancer is:

    • Indeterminate: No test performed, the result was indeterminate, or not a strong reading
    • Low: Genome is more stable
    • High: Lots of instability in the genome
  • TMB: Tumor Mutation Burden: This quantitative and qualitative measure of how many mutations have been identified in a specified tumor is an important biomarker for immunotherapy. It can be searched for using the Observation filter in the Subjects tab.

    TMB

    In the example above, 17.22 means 17.22 mutations per megabase of DNA sequence.

    • Low = 9 and under
    • Intermediate = 10-20
    • High = 21 and over

    The more mutations your cancer has, the more likely your immune system will recognize it as being foreign and will try to fight it off.

Omics Explorer Table

This table shows any data from Omics tests that has been ingested into the PHC. In some views, the data can be further filtered to fine tune your search.

Hyperlinks in the Omics Explorer Data Table link to the public annotation source.

Omics Home

Filters

Filters help fine tune your search through the available data. Filters are only available in the Omics Filtered View (Omics Summary is toggled off). They are found on the left side of the screen.

Table Column Headers

  • In the Omics Filtered View (Omics Summary is toggled off), most of the table column headers correspond with the filters on the left side of the Omics Explorer. Filters will only apply to the sequence type and the variant type (for example, filtering on the Somatic Short Variants).

  • In the Omics Summary view (Omics Summary is toggled on), the first 6 table columns are the most likely to populate data (CKB-Variant Type). The other table columns are for short variants and will be blank if it doesn’t apply to that variant type.

List of Table Column Headers: Most data in the Omics Explorer table is curated by LifeOmic except where noted below.

  • CKB – LifeOmic’s own internal database built from external sources (public data)
  • Gene – this hyperlink opens the ncbi site for that specific gene in a new window
  • AA Change: Amino Acid change
  • NC Change: Nucleotide change
  • Position: This is the DNA position in the genome where the mutation happened. The hyperlink opens a genome browser in a new window, such as ucsc

  • Variant Class (refers to missense, 3'UTR, intronic, etc.): Variant Class and Coding Effect overlap with the addition that Variant Class lists intronic and other non-coding variant classes. To filter for this, use the Coding Effect filter (as shown below).

    Coding Effect

  • Variant Allele Freq: Frequency the variant was detected in this sample (such as variant reads/total reads)

  • Zygosity: Heterozygous (HET), Homozygous variant (HOM), or Homozygous reference (REF)
  • Genomes Freq: Population frequency from gnomAD whole genome sequencing data
  • Genomes HOM: Number of people homozygous for the variant in the gnomAD whole genome sequencing data
  • Exomes Freq: Population frequency from gnomAD whole exome sequencing data
  • Exomes HOM: Number of people homozygous for the variant in the gnomAD while exome sequencing data
  • DBSNP RS ID: ID for the variant in the dbSNP database
  • ClinVar Significance: Clinical Significance reported in ClinVar from submitting labs
  • ClinVar Disease: Disease for which clinical significance was assigned in ClinVar
  • COSMIC Status: Status reported in the Catalogue of Somatic Mutations in Cancer (COSMIC)
  • COSMIC Count: Number of samples in COSMIC with the variant
  • Damaging %: Percentage of in-silico predictors (18 max) that predict the variant is damaging (for example, 9/18 = 50%)
  • Damaging Rank Score: The mean rank of the all in-silico predictors with value between 0-1,1 being most likely damaging and 0 being most likely benign.
  • Sift: One of the 18 in-silico predictors used and it's individual prediction. D = damaging, T = tolerated
  • MUT Taster: One of the 18 in-silico predictors used and it's individual prediction. D = damaging, T = tolerated
  • FATHMM: One of the 18 in-silico predictors used and it's individual prediction. D = damaging, T = tolerated
  • Gene ID
  • Transcript ID
  • Gene Class
  • Ref (provided by the sequencing result)
  • Alt (provided by the sequencing result)
  • Ref:Alt:Depth (provided by the sequencing result)
  • VCF Qual (provided by the sequencing result)
  • VCF Filter (provided by the sequencing result)
  • Coding Effect
  • EXON Number
  • Impact
  • Min Freq
  • Max Freq
  • ClinVar ID
  • ClinVar Review
  • ClinVar Submission
  • ClinVar Nearby
  • COSMIC ID
  • COSMIC Histology
  • COSMIC Site
  • COSMIC Nearby
  • IGV: Integrated Genome Viewer is a public tool. It’s useful for research and to validate if a mutation looks correct. Clicking the IGV icon in a row opens an IGV viewer (see below). BAM files (raw data)can be viewed in IGV.

    IGV Viewer

Omics Data Viewing Options

Data from Omics tests can be viewed either in a summary view (Omics Summary) or a filtered view (Omics Filtered View). Switching between these views is accomplished by toggling the Omics Summary ON and OFF (as seen in the clip below).

Omics Summary

Omics Summary

The Omics Summary view combines all the variants from a single test by sequence type and variant type into a single table for browsing.

Omics Filtered View

With the Omics Summary toggled OFF, the Omics Filtered View is displayed. This view breaks down the Somatic and Germline data into separate tabs/data tables and filtering is enabled.

  • Variants Types - The number beside each of these represents the number of variants present in this sample.

    • Short (single changes in the DNA such as 1 base change or small insertions or deletions)
    • Structural (rearrangement of the DNA such as translocation and inversion)
    • Copy Number (duplications or deletions of a large region)
    • Expression (RNA sequencing)

    Omics Variants

    This differs from the “Variant Count” found at the bottom left of the filters list (see image below). The variant count reports the number of variants matching the selected filters. (Filter options change based on which Variant Type is selected).

    Variant Count

Variant Match/Gene Match/Affects Alternate Transcripts

Omics Dots

Variant Match (green dot) – Refers to cancer knowledge base (CKB) and will show when you filter on CKB (seen primarily in Somatic Variant tab). This means there is an exact gene match for the Gene Name and AA Change in the CKB.

If we click on a Variant Match this will open the Variant Detail page. Here we can look at the CKB section and see the Variant Matches are listed first as these are exact matches. The Gene Matches follow and provide additional information.

Gene Match (purple dot) – Refers to the cancer knowledge base (CKB). The Gene Match means this gene is known to have a gene drug association which can be viewed on the Variant Detail page. -

Affects Alternate Transcript (blue dot) – A blue colored dot on the table means there may be other information or different transcripts (RNAs) for this gene, even though only the canonical transcript is displayed in the Omics Explorer Table to keep the table simple. To view the other transcripts/information, click on the row to open the Variant Detail page. Here you can scroll down to view the Alternate Transcripts.

Affects Alt Trans

In the clip above, there is a blue dot next to AA Change, if you hover over the dot, it shows the other positions for the AA change. There is also a blue dot beside Variant Class. This means the Variant Class shown is for the canonical transcript, but hovering over the dot will tell you there is evidence of it matching another variant class.

Access to More Data

In the top right corner of the blue header are three buttons that allow users to access more information regarding the subject and their test data.

File Buttons

  • View Test Detail Button The View Test Detail Button opens a page in a new browser window. This page is called Omics Tests and contains details of the test (see image below).

Omics Tests

  • View PDF in Files – If a lab report (pdf) from the sequencing lab is uploaded to the PHC, clicking this takes you to the Files User Interface so you can view the test files. Below is an example of a pdf test report.

PDF

  • Subject Viewer - Allows you to switch to the Subject Viewer page

Clinical Trial Matching

This feature helps look for clinical trials a subject would be eligible for. By default, it is turned off but can be turned on by LifeOmic. If enabled, it can be accessed by clicking the Trial Match icon in the top right corner of the blue header.

Trial Match icon

This takes you to the Clinical Trial Matching page (see below).

Trial Match Page

Match Input

The following is the info sent out to search for a match:

  • Birthdate
  • Gender
  • Zip Code
  • Disease for a subject
  • Biomarkers

Search Criteria

Clinical trial searches can be fine tuned with these options:

  • Zipcode search and Max distance from zip code
  • Exclude Disease Subtypes checkbox
  • Ignore Biomarker Criteria checkbox
  • Select the Trial Type from the dropdown menu
  • Select/Deselect individual variants (it only search on the ones selected)

After making any changes, click the Search for Trials button.

Trial Match Table

The Trial Match Table lists any matching trials this subject would qualify for. The list of trials is organized by nearest location.


  1. CancerScope: Grewal JK, Tessier-Cloutier B, Jones M, et al. Application of a Neural Network Whole Transcriptome–Based Pan-Cancer Method for Diagnosis of Primary and Metastatic Cancers. JAMA Netw Open. 2019;2(4):e192597. doi:10.1001/jamanetworkopen.2019.2597 


Last update: 2021-04-08