Clinical interpretation of variants based on ACMG Guidelines


ACMG Guidelines Implemented

The ACMG/AMP joint guidelines for variant interpretation provide a set of criteria to score variants and place them into one of five classification tiers. Following the guidelines requires deep diving into the annotations, genomic context and existing clinical assertions about every variant. VSClinical provides a tailored workflow to score each relevant criterion while also providing all the bioinformatic, literature and evidence from clinical knowledgebases to assist in the scoring and interpretation process.

Accelerated Interpretation

VSClinical is designed to allow variant scientists to efficiently process variants. It focuses on the optimal organization and presentation of the ACMG guidelines criteria as questions with supporting evidence and suggested answers. Previous classifications are automatically brought in, focusing effort on the set of novel variants that need to be scored for the first time. Most novel variants will be classified as benign or likely benign, and VSClinical is organized to quickly identify and classify these variants.

Variant Knowledgebase

The work done in your lab to classify variants will be automatically included in future analyses. As the number of samples processed increases, the number of variants requiring classification will be reduced as well as sample turn-around time. Previously classified variants will be marked with their last evaluation date, allowing them to be accepted in the context of the current sample without extra analysis time. If some critical external data surrounding that variant has changed since it was last evaluated, a flag will be raised to re-evaluate it in the updated context.

Automate Classification

While a final classification of a variant requires the manual inspection of the sample’s clinical details, published literature and the content of existing related clinical interpretations, many attributes of a variant and criteria from the ACMG guidelines can be auto-computed with bioinformatic algorithms and specially curated annotation sources. The ACMG auto-classifier algorithm can reduce the complexity of your annotation and filtering process, helping remove benign variants while highlighting potential pathogenic variants.

Standardize Lab Workflow

Any complex process leaves a lot of room for variation of execution by different lab personnel. VSClinical provides a guided workflow that reduces the amount of subjectivity to the variant classification and interpretation process. Standardized questions, automatically computed evidence, and historical context provides the framework for arriving at the final classification consistently and reproducibly.

Learn as You Go

New variant scientists will be able to start classifying variants with confidence using VSClinical’s integrated documentation and best practice excerpts. The guided workflow includes contextual explanations and descriptions of the specialized data sources and evidence brought in to answer scoring questions. We have carefully curated the published literature on ACMG guideline best practices, adaptations and clarifications.

Use Cases

Building on the powerful variant annotation and filtering capabilities VarSeq, a test-specific workflow can be configured to import, annotate, filter and prioritize the variants to be classified. Once configured, these steps are automatically run for any new batch of samples using the powerful VarSeq project template system. As part of VSClinical, the annotation and filtering process can be simplified by using the ACMG Auto-Classifier algorithm which collapses many annotation sources and computational prediction algorithms into a single integrated analysis. This compound algorithm will employ specialized strategies for loss-of-function variants, missense and splice site variants to determine their predicted impact. Clinical gene-level annotations such as OMIM allow for quickly sorting variants by the medical relevance to patient’s phenotype and expected inheritance model.
Once a set of candidate variants has been selected, an interpretation is started to score and classify the variants in the context of the current sample. Each variant is opened in VSClinical’s guided workflow with supporting evidence and recommended answers computed for each criteria question. Notes can be taken at the criteria level to document the manual scoring process and decision points. CLIA lab requirements are met by logging each user’s actions as it relates to scoring the variants.
After reviewing the questions for each relevant criterion, the ACMG classification rules are applied and a final interpretation can be saved to the lab-knowledgebase for the current sample and the analysis proceeds to the next variant. Once all the variants are finalized, the interpretation for the sample can be completed.
With all the variants processed for a sample, the lab can conclude the genetic test by aggregating the results into a clinical report. Additional sample and patient level information can be filled in, along with the variants selected from the interpretation process. The final report can be saved out to HTML or PDF. The VSClinical workflow goes from raw called variants in a VCF file to the final authoring of clinical reports, allowing a single solution to enable the genetic testing of NGS samples.

Recommended Learning Materials

We have a variety of supplemental learning materials that are an excellent resource for anyone interested in the industry or our software solutions. Here are some of our recommended materials for you to check out related to VarSeq!


Check out our free eBook on NGS-based clinical testing!

Download your copy here


Watch an informative webcast featuring VSClinical in action!

Introducing VSClinical - Streamlining ACMG Variant Interpretation Guidelines

Other Resources

Explore a clinical workflow in the VarSeq or follow along with a tutorial!

VarSeq Viewer:
Download Here

Introduction to VarSeq:
Download Here


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Technical Specifications


4 GB of RAM

Multicore CPU

100GB of space available for annotations and projects


If you are working with whole exomes or genomes, especially if or hundreds to thousands of samples, we suggest a high-memory configuration and plenty of storage capacity:

16GB+ of RAM (32GB for Servers)

8+ CPU Cores

1TB of space available for annotations and projects


The following operating systems are supported:

64-bit Windows 7 or later (32-bit also supported, but not recommended)

Linux Ubuntu 14.04 or later (64-bit only)

Linux RHEL 6 or later, or equivalently CentOS 6 or later (64-bit only)

Mac OS X 10.9 or later


Golden Helix VarSeq and SVS can be configured to access the internet through a SOCKS5 or HTTP/HTTPS Tunneling Proxy. Go to Tools -> Proxy Settings… to configure.

The software only needs to make outgoing connections on standard HTTP/HTTPS ports and protocols. If a local firewall is installed that prevents these types of outgoing connections (this is very uncommon), firewall rules will need to be created to whitelist the software.

Note we have run into numerous issues where aggressive anti-virus programs prevent the product from performing normal operations such as opening files and logging in. You may need to whitelist Golden Helix executables or disable these tools to perform your analytics.