Pathology Organizations Published Recommendations for In Silico Approaches for Validating NGS Analysis Pipelines

• AMP, API, and CAP released recommendations for in silico approaches for validating Next-Generation Sequencing (NGS) analysis pipelines.  
• In silico approaches for NGS, data modeling has utility in the clinical laboratory as a tool for clinical assay validation.  
• The report reviews, analyzes, and presents the latest data to help guide clinical laboratory professionals on when and how to use these critical supplementary in silico data approaches.  

Organizations from the pathology landscape released a report offering recommendations for using in silico approaches for validating Next-Generation Sequencing (NGS) data analysis pipelines. 

This manuscript is a joint report of the Association for Molecular Pathology (AMP), the Association for Pathology Informatics (API), and the College of American Pathologists (CAP). 

In silico approaches for NGS data modeling has utility in the clinical laboratory as a tool for clinical assay validation. In silico data enables the simulation of a range of variants that may be difficult to obtain from a single physical sample. This data allows laboratories to test the performance of clinical bioinformatics pipelines more accurately without sequencing additional cases. 

According to AMP Co-Chair of the In Silico Pipeline Validation Working Group, Justin Zook, the association convened a panel of subject matter experts of the three organizations to explore the advantages and disadvantages of these various types of in silico data. The report summarized vital findings and provided valuable recommendations to help clinical laboratory professionals select the most appropriate format for their specific purposes. 

“As more laboratories around the country use in silico data to simulate variants to help validate the performance of clinical NGS data analysis pipelines, clinical laboratory professionals may need aid for understanding both the value these methods bring and the important nuances and limitations of these approaches,” Zook added. 

Here are some critical recommendations for the use of in silico approaches for validating NGS data analysis pipelines:  

•  The laboratory may use in silico data files to supplement NGS analytical validation, particularly to assess analytical sensitivity or false negative rates for specific variants. However, in silico data files cannot supplant the use of physical samples.  
• The laboratory should understand the functional limitations of the type(s) of in silico data.  
• Commercial vendors and internal pipeline developers should include options in their analysis pipelines to facilitate easier in silico data file import and analysis by clinical laboratories. 
• The laboratory may consider using in silico samples for minor updates to clinical bioinformatics software pipelines. 

• The laboratory should understand the limitations of most in silico data for assessing performance in particular genome contexts and variant types susceptible to systematic sequencing and mapping errors. 

The report reviews, analyzes, and presents the latest data to help guide clinical laboratory professionals on when and how to use these important supplementary in silico data approaches. AMP Co-Chair of the In Silico Pipeline Validation Working Group, Eric J. Duncavage, “we intend to review and update these consensus recommendations as new data and other in silico methods become available,” stated. 

Read the complete report here: https://doi.org/10.1016/j.jmoldx.2022.09.007   

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