To streamline case review, the AI Shortlist pre-selects the list of variants likely to be causative for each case:

Most Likely Candidates

Variants that are most promising for solving the case. This list is limited to 10 top-scored variants but may include more if more than one variant is tagged per gene (suggesting compound heterozygosity). We can change the Most Likely Candidates number limit upon request.

Candidates

Several dozen highly scored variants worth considering.

As of version 30.0 and onwards, the ranking of variants by AI Shortlist considers both SNVs and CNVs, including SNV + CNV compound heterozygotes. Starting from version 32.0, AI Shortlist additionally considers SVs, mtDNA variants and STRs.

The AI Shortlist rates variants based on predicted variant effects, alternative allele frequency, familial segregation pattern, phenotypic match, in silico predictions, and other relevant information from scientific papers and databases.

During the case review, you can untag variants selected by the AI Shortlist or manually tag ones not selected by the AI Shortlist.

The Candidates tab presents:

Most Likely Candidates and Candidates

A shortlist of the most promising variants with the highest scores from the AI Shortlist:

• before 30.0: SNVs;

• 30.0+: SNVs and CNVs;

• 32.0+: SNVs, CNVs, SVs, mtDNA variants and STRs.

These variants are initially selected by the AI Shortlist, but you may untag variants or tag them manually during the case review.

Incidental

Pathogenic or likely pathogenic variants in the medically actionable genes defined by the ACMG. These variants are automatically tagged only if you've selected the Secondary findings checkbox while creating a case.

Carrier

Variants identified by the Carrier analysis pipeline. Carrier variants are automatically tagged only if you've selected the Carrier Analysis checkbox while creating a case. Analysis requirements and a list of targeted regions are specified by the organization's manager. This Carrier analysis flow is implemented by request.

In Report and other custom variant tags

Variants that were manually selected to be reported.

Reviewing the Candidates tab

To select variants with a particular tag, use the Filter candidates dropdown menu in the top right corner. You can choose between Most Likely, Candidate, Incidental, Carrier, Not Reviewed, or any custom tags used in your organization.

For each variant on the Candidates tab, you can explore the suggested diagnosis, gene symbol, main variant details, and variant tag.

When a variant is found in a gene with no known association with a disease, the possible diagnosis cannot be indicated. Such variants are displayed under the Gene of Unknown Significance title.

All the relevant Most Likelies and Candidates fitting a сompound heterozygous mode of inheritance are presented together. This refers to both confirmed and assumed compound heterozygosity (cases with at least one parent and singleton cases, respectively).

If you want to inspect the complete variant information, click on the variant bar to continue to the Evidence page. You can visualize evidence in text or graphical format (Click on the interactive text in the top left corner: Show evidence as text or Show evidence graph to toggle between the two).

The Variant table:

• Displays the analysis results, one variant per row;

• Supports variant search and sorting by various criteria;

• Allows downloading of up to 1500 filtered variants;

• Enables users to manually add variants to a delivered case.

Variant table legend (34.0+)

Starting from version 34.0, the formatting of variant table rows provides hints about the variant status for the current user per particular case. It indicates whether the variant has been viewed by the current user, and whether it has been tagged either by the current user or by the AI Shortlist.

Tagged vs not tagged variants:

• Not tagged variants are indicated by black font color;

• Variants tagged by the AI Shortlist are indicated by green font color;

• Variants tagged by any user, whether currently active or another user, are shown in blue font color.

Viewed vs not viewed variants:

• Variants viewed by the current user are indicated by regular font weight. The variant is marked as viewed only if the current user has opened the variant page before the case was finalized.

• Not viewed variants are indicated by bold font weight.

The table view is customizable:

1. Columns can be dragged-and-dropped.

1. Any column can be shown or hidden by selecting the columns in the Show/Hide Columns menu (activated via an icon on 30.0.0+) in the top right corner of the page.

1. You can choose between comfort and compact view by pressing the button next to the Variant search tab.

All modifications are automatically saved for each individual user and retained until new changes are made.

You can enter a specific case from the Cases page by clicking Full details in the corresponding row of the case table.

The Individual case page includes:

Top bar

Displays a Case ID and Case status and includes Case interpretation, Edit case info, and Report preview buttons.

Candidates tab

Highlights a shortlist of variants, suggested to be reviewed first - Most Likely Candidates and Candidates.

Lab tab

Illustrates quality metrics for the sequenced samples.

Analysis tools tab

Provides numerous customizable filters to help you explore the total list of genetic variants in compliance with your organization's standard case review process. You can export shortlisted variants in .xlsx format.

Versions tab

Documents versions of all the resources used during case analysis.

You can search for variants in the Variant search box by:

Single phenotype

"phenotype1" (e.g., "Mandibular prognathia")

Disease

"disease1" (e.g., Kabuki syndrome 1)

Disease inheritance mode

"inheritance mode1" (e.g., Autosomal dominant);

Genomic position

"coordinate1" (e.g., chr11:2686616)

Specific SNV/indel variant (32.0+)

"variant" (e.g., chr1:27089776G>T)

Genomic range

"range1" (e.g., chr11:2686616-2886620)

CNV length

"cnv_size:size1" (e.g., cnv_size:100000-10000000)

Gene symbol

"gene1" (e.g., BRCA1)

Multiple gene symbols added in batch

"gene1, gene2, gene3" (e.g., BRCA1, BRCA2, UBE3A)

Most of the above-listed options may be combined.

To do this, click on the Export icon on top of the .

When you:

• Complement NGS with other genetic tests done on the side (long-read sequencing, optical mapping, CGH, SNP array, karyotyping/FISH, repeat-primed PCR, MLPA, Southern blot, etc), or

• Choose to report a few adjacent variants as a single multi-nucleotide variant,

the need to add variants on top of the analysis results arises.

You can manually add variants absent from the VCF or not called from the FASTQ. Supported variant types are SNV, CNV, UPD, ROH, and STR. SV is coming soon!

To manually add a variant:

1. In the Manually Add Variant window select variant type among SNV, CNV, UPD, ROH, and STR.

2. Fill in variant details according to the selected variant type:

1. Click on Create Variant.

Manually added variant's Variant page

To filter by manually added variants:

The Emedgene Workbench offers a wide array of dynamic filters to help reveal or limit variants that are the most relevant to your clinical case. Each filter contains multiple options to customize the case review process according to your organization's best practices.

The Filters/Presets panel includes two tabs:

• : Manually adjustable variant specifications;

• : These are filter combinations that are custom-built and implemented according to the case analysis SOPs used by your team.

The Analysis tools tab contains multiple tools that facilitate a case review:

• - includes numerous adjustable Filters and Presets (on the left)

• - a user-customizable display of all the analysis results (core section)

• - when selecting a variant, the variant page opens, revealing a detailed annotation and other assessment tools for the particular variant.

Variants can be filtered by:

• : Variant quality metrics

• : Alternative allele frequencies and genotype counts in public and internal databases

• and : Variant consequences, ACMG pathogenicity classes, variant types (sequence, structural, mtDNA), and whether and how the variant is classified in clinical variation databases.

• : Disease-associated genes, genes of unknown significance, ACMG clinically actionable genes, cancer-associated genes, candidate gene list, etc.

• : Gene-disease associations that match the proband's clinical phenotypes

• : Select a mode of inheritance that is compatible with the genotypes and phenotypes of affected and healthy family members

• : Filter by genotypes in selected samples

• : Variants tagged by the user or the AI Shortlist, manually added variants, and other organization level filters.

In the Filters tab of the Filters/Presets panel, the vertical ellipsis button offers options:

• Clear - deselect all filters and reveal all the variants;

• Reset to Default - set default filters values: moderate/high quality (Quality Filter), low/moderate/high severity (Variant Filters), and Het/Hom zygosity in the proband (Zygosity Filters);

Variant table columns:

The Quality Filters allow one to filter variants by variant quality metrics. The filter can operate in a Simple or Advanced mode.

Modes

Simple

Select a minimum degree of sequencing Quality (Low, Moderate, High).

Advanced

For SNVs and Indels:

• Select a minimum degree of sequencing Quality (Low, Moderate, High),

• Define minimum Mapping Quality (0-60 - value can be exceeded using the text box),

• Specify minimum Depth (0-500 - value can be exceeded using the text box),

• Set minimum number of alternate reads in Alternate Read (0-500 - value can be exceeded using the text box). Note: available for cases run with pipeline version 5.26+.

• Set limits on Allele bias (0-100). Note: when applied to mtDNA variants, the Allele bias filter operates on heteroplasmy levels.

For CNVs:

• Set limits on CNV Length (50bp, 1kb, 10kb, 100kb, 1Mb, 100Mb, Max CNV length),

• Set minimum CNV Bin Count (1, 5, 10, 25, 50, 100, 500).

Default values

When Filters are Reset to Default, The Quality Filters are set to:

• Quality: Moderate and High,

• Mapping Quality ≥45,

• Depth ≥ 10,

• Alternate Read - no filtering,

• Allele bias - no filtering,

• CNV Length - no filtering,

• CNV Bin Count - no filtering.

As of version 2.26:

Presets are combinations of Filters that match your case analysis SOPs.

For versions prior to 34.0, technical support is required to implement a customized filter Preset. But with version 34.0 and later, users can easily do it on their own.

Create filter Presets from active filters (34.0+)

To save Presets from active filters:

1. Open the Filters panel and navigate to the Filters tab;

2. Click on the three-dot icon;

3. Select Save as preset;

4. Enter a name for the Preset (Note: Avoid using non-Latin symbols that don't follow the ISO-5589-1 standard);

5. Click Save.

Where can I manage Presets? (34.0+)

To manage filter Presets, navigate to Settings > Organization Settings > Lab Workflow > Presets. From here, you can edit, delete, or lock/unlock the preset as needed.

Create filter Presets from your gene lists (32.0+)

1. In Presets, scroll down and click Add beside Gene Lists.

1. Select the gene lists you want to utilize as filter presets by marking the relevant checkboxes. Starting from version 30.0+, a search bar simplifies list navigation by allowing you to search by list name.

1. Click Save.

Presets originating from gene lists will appear in Presets under Gene Lists.

Review logic behind the Preset (32.0+)

On 32.0+, for a quick refresher, you may review the logic behind each Preset directly within your analysis flow. To do so, click on an downward arrow icon left to the Preset's name.

You can implement different combinations of Presets to be used for different case types (i.e. Presets for exome may be different from Presets for genome) as defined by your SOPs to further streamline case review.

The combination of Presets is referred to as a Preset group.

Select a Preset group to display in the case

Preset group selection is available in the Case info screen of the Add new case flow while creating or editing a case.

Where can I manage Preset groups? (34.0+)

To manage filter Preset groups, navigate to Settings > Organization Settings > Lab Workflow:

Preset groups

From here, you can create (from Presets/from a JSON file, edit, hide/unhide and download Preset groups as needed.

Default Preset group

Here, you can set a Preset group as default, so it will be used unless another Preset group is selected during case creation.

The Variant Type Filters allow filtering variant list by variant type:

• Sequence variants: SNV, Indel (Note: Indel filter requires pipeline version 5.22.8 or higher);

• CNV: DEL, DUP;

• mtDNA SNV/Indel.

The Variant Effect Filters allow filtering variants by consequence, ACMG pathogenicity classes, and whether/how the variant has been classified internally or in clinical variation databases. The filters can operate in a Simple or Advanced mode.

Modes

Simple

Filter variant list by:

• Severity of variant effect (High, Moderate, Low, Modifier);

• CNV Severity is set according to the image below;

• Known Variant (Known Variants, Known Pathogenic Variants) - variant status in clinical variation databases (ClinVar, HGMD) and previous classifications by your organization or network.

Advanced

Further restrict analysis results by:

• Specific Main effect of the variant on protein structure and function;

• ACMG Classification (Pathogenic, Likely Pathogenic, Uncertain Significance, Likely Benign, Benign)- ACMG pathogenicity class assigned manually or automatically. Note: applicable only for Candidate and Most Likely variants;

• ClinVar Known Variants (Pathogenic, Likely Pathogenic, VUS, Likely Benign, Benign, Other) - variant status in ClinVar;

• Custom database Known Variants (Pathogenic, Likely Pathogenic, VUS, Likely Benign, Benign, Other) - variant status in your own curated variant database, including CNVs detected by means of NGS and/or chromosomal microarray;

• Manually Classified Variants - select this option to restrict results to variants from previous cases with user-assigned Pathogenicity.

Default values

When Filters are Reset to Default, the Variant Filters are set to:

• Severity: High, Moderate, Low;

• Known Variant - no filtering.

The Top bar in the Individual case page indicates the Case ID and current Case status.

Options available through the Top bar:

• Change the Case status

• Reanalyze the case

• Finalize the case and write interpretation notes

• Edit the case info

• Preview the case report

Multiselection of variants:

1. Hover over a variant to reveal a checkbox at the start of the line;

2. Checking the box exposes the Multiselect actions bar which replaces the Search bar, and checkboxes appear for all variants in the current view;

3. Manually select variants one by one or check the Select all checkbox. Note: the Select all function applies solely to variants displayed on the current page, not all variants matching the active filters.

Bulk actions:

1. View/un-view variants

How to change the review status for multiple variants at once:

1. Select variants of interest;

2. In the Multiselect actions bar, click on the Viewed icon and select Viewed or Un-viewed. Note: user-tagged variants can’t be un-viewed.

2. Assign/remove tags

How to assign a tag to multiple variants at once:

1. Select variants of interest;

2. In the Multiselect actions bar, click on the Tag icon and choose a tag from the dropdown menu. Note: If any variants already possess tags, a warning message will appear. Click on Apply to proceed.

How to remove tags from multiple variants at once:

1. Select variants of interest;

2. In the Multiselect actions bar, click on the Tag icon, then click on:

   1. Clear to remove user-assigned tags, or

3. Assign/clear pathogenicity

How to assign pathogenicity to multiple variants at once:

1. Select variants of interest;

2. In the Multiselect actions bar, click on the Pathogenicity icon and choose a pathogenicity class from the dropdown menu. Note: only tagged variants can have pathogenicity assigned.

How to clear pathogenicity from multiple variants at once:

1. Select variants of interest;

2. In the Multiselect actions bar, click on the Pathogenicity icon, then click on Clear.

The Gene Filters allow filtering variants by genes or specific regions:

• All Disease Associated Genes - variants in the genes with a published disease association;

• All Unknown Genes - variants in the genes of unknown clinical significance;

• Candidate Genes - variants in a Gene list if defined during case creation;

• All ACMG genes - variants in the clinically actionable genes defined by the ACMG:

  • Versions 30.0+: 81 genes (Miller et al. 2023);

  • Versions <30.0: 78 genes (Miller et al. 2022).

• Cancer Associated Genes - variants in genes with published association with oncological disease;

• LoF Genes (Emedgene Knowledgebase 26+) - variants in extremely LoF intolerant genes (gnomAD pLI ≥ 0.9). Note: if a variant is a CNV that overlaps more than one gene, it will appear in the filtering results if at least one of the genes has gnomAD pLI ≥ 0.9);

• Established HI/TS Genes (Emedgene Knowledgebase 26+) - variants in genes with sufficient evidence of dosage sensitivity (defined by having ClinGen's Haploinsufficiency and/or Triplosensitivity scores of 3);

• Coding regions - variants restricted to the protein-coding sequences.

• In Targeted Regions - variants in the regions defined by the Enrichment Kit selected while creating a case.RefSeq coding regions will be used as a reference if no kit is provided.

Default values

When Filters are Reset to Default, the Gene Filters remain disabled, except for cases launched in Virtual panel mode of the Gene list. In such a case, the Candidate Genes filter is activated by default.

The User Filters allow filtering by variant tags assigned by the user or AI Shortlist:

• With Notes – variants that are accompanied by Variant Interpretation notes. This filter returns all the automatically and manually tagged variants, except those with manually removed Variant Interpretation notes (if any).

• Submitted for Sanger confirmation – variants manually assigned as eligible for Sanger sequencing in the Variant page's Evidence section.

• Manually added variants - variants added manually on top of the analysis results.

• Most Likely – variants tagged as Most Likely by AI Shortlist or by the user.

• Candidates – variants tagged as Candidate by AI Shortlist or by the user.

• Incidental – variants tagged as Incidental by AI Shortlist or by the user.

• Carrier – variants tagged as Carrier by AI Shortlist or by the user.

• Not Relevant – variants manually tagged as Not Relevant.

• My Tags – variants tagged by the current user.

• AI Shortlist (Auto Analysis) - variants tagged by the AI Shortlist.

• With Pathogenicity Tag – variants with Pathogenicity manually assigned in the Variant page's Evidence section.

The Zygosity Filters enable manual selection of zygosity status (Het, Hom, Ref, No Cov) for each sequenced sample in the pedigree.

The Inheritance Filters allow filtering variants using an assumed inheritance mode that is consistent with the segregation of genotypes and phenotypes in the family.

The Inheritance Filters are primarily relevant for cases with sequencing data for a trio pedigree and less relevant for singletons. For large and complex pedigrees, consider using Zygosity filters that are more flexible.

You can filter for:

• Autosomal Recessive - Homozygotes. Autosomal variants that are Hom in the Proband and other affected family members (if any) and Het, Ref, or No Cov in the unaffected members.

• Autosomal Recessive - Compound Heterozygotes. Two or more autosomal Het variants in the same gene inherited from different parents.

• X-Linked Recessive. X-chromosome variants in a male Proband (i.e. Hemi) that are Het in his unaffected mother.

• X-Linked Dominant. X-chromosome variants that are Het in affected females in the pedigree.

• De Novo Dominant. Autosomal and X-chromosome variants that are Het in the Proband and Ref in parents.

• Autosomal Dominant. Autosomal variants that are Het in the Proband and other affected family members but Ref in healthy relatives. ​

With the Display No Coverage slider, you can control whether to include or exclude variants that are No Cov in Proband or any other sequenced sample in that pedigree.

The Phenomatch Filters highlight variants located in the genes whose phenotypic annotation matches the proband's clinical presentation.

When one of the Phenomatch Filters is active, the results are limited to the variants that are top-rated by the corresponding algorithm:

• Phenomatch - High Specificity – strictly filters genes with disease phenotypes matching the exact patient HPO phenotypes.

• Phenomatch - Powered by AI – filters genes with disease phenotypes loosely matching the patient HPO phenotypes.

• Phenomeld (30.0+) - the latest and most refined phenotypic matching model based on Phenomatch - Powered by AI.

• Phenomatch with Unknown – filters genes of unknown significance based on indirect links to patient phenotypes (including mouse models, gene families, pathways, etc.).

On the , each proband's phenotype is marked according to the degree of similarity to the phenotypes observed in the genetic condition presumably associated with a variant under review.

Phenotypic match strength levels:

Exact match

Same term as in the clinical synopsis of the suspected disease

Match by ascendance

Phenotypes share a parent term in the HPO hierarchy

Indirect match

Phenotypes are closely related in the HPO hierarchy, but term relatedness is lower than in Match by ascendance

Unmatch

The phenotype is not reported for the suspected disease.

Each phenotypic match strength level is denoted by a particular icon next to the HPO term in the Case info tab of the :

If you would like to update or make corrections your case details, phenotypes or gene list, you have the option to edit the case and save or reanalyze the data.

How to edit case data:

1. Open a ,

2. Press Edit case info button in the top right corner,

3. You'll access the flow. You can edit any information on the Family tree screen, as well as Select genes list, Select preset, and Additional case info sections of the Case info screen.

1. After you've finished editing the case and pressed Next in the Case info screen, a window will pop up:

The Versions tab reports versions of all the tools and resources used during the case analysis in the following categories:

• Annotation

• Emedgene Resources

• Knowledgebase Sources

• Organization Local Databases

• Population Databases

• Variant Databases

​

The Polymorphism Filters enable filtering variants by alternative allele frequencies and genotype counts in public and internal databases. The filters can operate in a Simple or Advanced mode.

Modes

Simple mode

Switch on or off Display Polymorphism option:

• When switched on, no restrictions are being applied.

• When switched off, variants with allele frequency >0.05 in public databases or >0.25 in the EmedgeneDB are filtered out.

Advanced mode

Filter variant list by limiting the maximum Allele Frequency, Hom/Hemi and Het counts in one of the public database options (GnomAD, ExAC, 1000 Genomes, or GME) or, by default, in all (All Databases). The default values for Hom/Hemi and Het can be exceeded using the text box.

In addition, limit results by the maximum Allele Frequency in internal databases:

• Emedgene Database - a static sample set of 806 healthy individuals. Aimed at getting rid of the artifacts generated by our FASTQ processing pipeline

• Organization Databases, e.g., NoiseDB - a blacklist of variants (implemented by request).

Default values

When are Reset to Default, The Polymorphism Filters are set to the Display Polymorphism option of the Simple mode, i.e., no filtering.

The finalized case status locks the case to prevent further changes to interpretation notes, ACMG tags, variant tags, pathogenicity and case-level interpretations.

How to finalize a case:

2. In the Case interpretation widget, indicate the final result of the analysis:

1. Confidently Solved (Positive),

2. Likely Solved (Positive),

3. Further Investigation (Uncertain), or

4. Unsolved (Negative).

The indicated case analysis outcomes are used to calculate the diagnostic yield.

You have the flexibility to reorder variants by drag-and-drop. The order of variants will be preserved in the Clinical Report within each variant table and/or section, defined by a variant tag and a variant type (e.g. SNVs tagged "In report").

In Gene Interpretation, you can import gene annotation from Curate (30.0+).

5. To complete the Case interpretation flow, press Save.

You can download the report preview in a .pdf or .odt format.

All the generated reports are saved per case and each can be downloaded in a .pdf or .odt format.

The Lab tab displays sample quality in the following sections:

Summary dashboard

highlights the key sample quality indicators, with more details provided in the subsequent sections.

Sequencing lab information

reports sequencing run technicalities as indicated during case creation:

• Lab

• Instrument

• Reagents

• Kit type

• Expected coverage

• Protocol

Case quality (34.0+)

provides a broad overview of the case quality:

Chromosome validation

Ensures each chromosome has a minimum of one variant with high quality.

GnomAD validation

Ensures each chromosome has a minimum of one variant annotated with GnomAD.

1. ClinVar validation

Ensures each chromosome has a minimum of one variant annotated with ClinVar.

Auto analysis validation

Ensures at least one variant has been tagged by the AI Shortlist.

mtDNA reference validation

Sample quality

highlights metrics for each sample:

Quality

Overall sample quality indicator based on the average depth of coverage for the indicated kit (or RefSeq coding regions if no kit is provided), percentage of bases covered >20x, error rate, percentage of reads mapped to the reference sequence, and presence of contamination.

Sex validation results

Sex validation (called "gender validation" in versions before 33.0) is performed by comparing the observed homozygous/heterozygous genotype ratio on the X chromosome with the expected ratios for females (<2) and males (>2). Only high-quality Single Nucleotide Variants (SNVs) in the targeted regions specified by the kit (or RefSeq coding regions if no kit is provided) are considered. It is crucial to note that a minimum of 50 variants is required for accurate sex validation. Importantly, if we lack 50 high-quality SNVs, sex validation would not be performed, resulting in an "empty" return. For sample where sex was designated as "unknown" during case creation, the sex validation will present the "predicted" sex.

Ploidy estimation results (32.0+)

Specific quality parameters

Average coverage, bases with coverage >20x, error rate, % mapped reads, etc. Blue bars represent each of these parameters per sample, while a vertical line represents a general metric across all the samples across all the cases in the account.

Detailed QC metrics can be downloaded upon clicking on the download icon next to the section title.

Pedigree

For each possible pair of samples in a pedigree, the declared family relation is compared with the observed relatedness coefficient. The relatedness coefficient is calculated from the percentage of shared alleles and the size of the Identity By Descent blocks. IBS0 indicates the number of sites lacking shared alleles. This metric can help differentiate between sibling-sibling and parent-child relationships when both are expected to have ~50% relatedness.

When the relatedness coefficient for a parent-child pair or a full sibling pair falls outside the range of 40 to 60%, the relatedness check is considered failed.

If the relatedness coefficient indicates a very low chance of shared ancestry, it is classified as 'Shared Ancestry' (0.2%-4%). For relatedness coefficients that suggest closer genetic ties, it results in 'Consanguinity' (4%-15%). When the genetic similarity reaches a high threshold (>15%), it not only results in 'Consanguinity' but also triggers a warning/ 'Failed' quality.

Genes with insufficient coverage

Here, you can directly check if your genes of interest have been entirely covered. Consider using Sanger sequencing to cover gaps in the genes of interest.

To examine if the gene contains regions with insufficient coverage:

1. Enter a gene symbol in the search box and select it from the dropdown.

2. From the Coverage dropdown menu, choose between ≤0x, ≤5x, ≤10x, ≤20x, and ≤All.

3. You can Download insufficient regions or explore them in the table. Pressing the More details button will open a pop-up window specifying the genomic coordinates of the poorly covered regions.

Simply click the Add Gene List button and select any of your pre-loaded gene lists.

You may further filter regions

by the maximal depth of coverage and the maximal percentage of bases covered greater than 20x.

1. Click on More details:

1. In the pop-up window click on View on IGV:

The Evidence page presents the most relevant evidence behind the automatic variant classification suggested by the AI Shortlist.

This view can be generated for any other variant after the variant has been manually .

The Evidence page is accessible from:

Click on the variant bar.

View modes

You can switch between the graph and text view by clicking on the link on top of the page (Show evidence graph or Show evidence as text, respectively). The graph view is helpful for exploring the data, while the text view is relevant for collecting notes.

AI Shortlist collects data from credible studies and public databases in an internal knowledge base that maps complex connections between variants, genes, mechanisms, diseases, and phenotypes.

The Evidence page provides concise evidence for the specific variant, including:

Variant information

The main effect of the variant, its HGVS nomenclature for coding DNA and protein changes, and zygosity, including if the variant is de novo.

Gene information

Gene symbol, if the gene is tolerant to variation, and assumed inheritance mode in the case under review. This is suggested based on the observed level of genotype-phenotype co-segregation and inheritance mode of the genetic condition (reported or suspected).

In addition to the conventional inheritance modes (Autosomal Dominant, Autosomal Recessive, Compound Heterozygote Autosomal Recessive, X-Linked Dominant, X-Linked Recessive), the platform also employs Autosomal Dominant Partial Penetrance and Partial Autosomal Recessive designations.

Autosomal Dominant Partial Penetrance is used when the gene-associated condition is AD, and the variant is Het in the test subject and at least one of their parents. This suggests that the phenotypes may be due to incomplete penetrance of the genetic condition.

Partial Autosomal Recessive is used when the gene-associated condition is AR and the variant in the test subject is Het. This helps to account for the possibility that another causative variant is undetected - in the same (compound heterozygosity) or another (digenic inheritance) gene.

Disease information

Condition name as suggested by OMIM, other disease databases or in the literature.

Patient Phenotypes

Proband's phenotypes that match phenotypes reported for the suspected disease. Exact, indirect, and matches by ascendance are considered.

Unconfirmed Disease Phenotypes

Phenotypes reported for the suspected disease but not observed in the proband.

Unmatched Patient Phenotypes

Phenotypes observed in the proband but not known to be manifested as part of the suspected disease.

Links

Follow the links to the primary sources to explore the evidence further. The links are in the References section (text view) and are accessible by hovering over the arrows (graph view).

Edit mode

The evidence graph can be manually edited to include additional evidence for the case's resolution. To enter the edit mode, click on the pencil icon in the top left corner of the page. In this mode, you can edit, add, and delete text boxes.

With Emedgene's reporting solution, creating comprehensive Clinical Reports is a piece of cake.✨ All the relevant case- and variant-level information is automatically populated to the corresponding sections of the report.

Exemplary Clinical Report layout and information sources

Case Information

Includes (numbers indicate ):

1. Patient details: Patient's name [1], date of birth [2], sex [2] and MRN [1];

2. Technical sample details: Specimen's type [1] and quality [3], dates collected [1] and received [1];

3. Provider details: Lab number [1], ordering physician's name [1];

4. Report date [3];

5. Case type [2];

6. Clinical information: Indication for testing [2] or, if it's not available, Proband's phenotypes [2]; Secondary findings requested [2]: Yes/No.

Results summary

Results summary gives a general overview of the test result:

1. Test result summary [4];

2. Secondary ACMG findings summary [4];

3. Interpretation summary [4];

4. Recommendations [4].

Detailed results

Detailed results highlight the genetic testing findings:

1. Basic sequence variant details:

   1. Gene [3],

   2. Genomic location [3],

   4. Zygosity/Inheritance [3] (Zygosity in Proband and their relatives),

   5. Classification [6] (Pathogenicity),

   6. Condition [7] (Disease and Inheritance mode if available).

2. Basic copy number variant details:

   1. Chromosome region [3],

   2. Type: DEL/DUP [3],

   3. Genes [3],

   4. Zygosity/Inheritance [3] (Zygosity in Proband and their relatives),

   5. Minimum length [3],

   6. Classification [6] (Pathogenicity).

3. Individual sequence variant interpretations:

   1. Basic variant details [3]: gene, genomic location, coding sequence and protein sequence change HGVS notations, exon involved, variant's main effect, Prediction, Conservation and Splice Prediction scores, gnomAD population statistics,

   2. Associated diseases [3] - all the diseases known to be associated with the gene,

   3. Quality [3]: Zygosity, base quality, depth in Proband and their relatives,

   4. Summary [8].

4. Individual copy number variant interpretations:

   1. Chromosome region [3],

   2. Type: DEL/DUP [3],

   3. Minimum length [3],

   4. Zygosity in Proband [3],

   5. Classification [6] (Pathogenicity),

   6. Summary [8].

5. Gene interpretation [4]

Test details

Test details:

1. Test methodology [5];

2. Test limitations [5].

References

The References [9] section lists all the PubMed citations mentioned in the report. References will be auto-formatted if the PMID is supplied in the report.

Signatures

The Signatures section documents who and when generated the report [3].

Generating a Clinical Report

Data sources

[1] - API;

[3] - automatically inferred by Emedgene,

[5] - fixed text,

[9] - in any of the free text fields you can add PMIDs in one of the following formats: PMID1234, PMID 1234, PMID:1234.

You can expand to a broader genetic testing option if the results of more targeted testing are inconclusive. You may reflex from Custom Panel to Exome or Genome, or from Exome to Genome.

To do this, you should change the Case type in flow, thereby rerunning using the broader analysis.

Calling methodology

Emedgene uses ExpansionHunter by DRAGEN to call short tandem repeats (STR), also known as repeats expansions.

Thirty clinical genes associated with diseases caused by repeat expansion are called in and presented in the platform. Those genes are: AFF2, AR, ATN1, ATXN1, ATXN10, ATXN2, ATXN3, ATXN7, ATXN8OS, C9ORF72, CACNA1A, CBL, CNBP, CSTB, DIP2B, DMPK, FMR1, FXN, GIPC1, GLS, HTT, JPH3, NIPA1, NOP56, PABPN1, PHOX2B, PPP2R2B, RFC1, TBP, TCF4.

STR calling with ExpansionHunter

Spanning reads

Exact sizes of short repeats are identified from spanning reads that completely contain the repeat sequence.

Flanking reads

When the repeat length is close to the read length, the size of the repeat is approximated from the flanking reads that partially overlap the repeat and one of the repeat flanks.

In-repeat reads (IRRs)

If the repeat is longer than the read length, its size is estimated from reads completely contained inside the repeat (in-repeat reads). In-repeat reads anchored by their mate to the repeat region are used to estimate the size of the repeat up to the fragment length. When there is no evidence of long repeats with the same repeat motif elsewhere in the genome, pairs of in-repeat reads can also be used to estimate the size of long (greater-than-fragment-length) repeats.

Recommendation for interpretation

In light of our recent experience and an internal investigation by the Illumina’s scientific team, we believe it is appropriate to enable prioritization for a subset of STR loci, but not all loci typed by DRAGEN. This is due to technical genotyping challenges and/or lack of scientific evidence of pathogenicity for the remaining loci. Current list of genes where STR may be tagged when appropriate is provided below: