A Model Study of In Silico Proficiency Testing for Clinical Next-Generation Sequencing.

Arch Pathol Lab Med

From the Departments of Pathology (Drs Duncavage and Pfeifer) and Genetics (Dr Abel), Washington University School of Medicine, St Louis, Missouri; the Department of Pathology (Dr Merker), Stanford University School of Medicine, Stanford, California; Product Development, Laboratory Improvement Progr

Published: October 2016


Category Ranking

98%

Total Visits

921

Avg Visit Duration

2 minutes

Citations

20

Article Abstract

Context: -Most current proficiency testing challenges for next-generation sequencing assays are methods-based proficiency testing surveys that use DNA from characterized reference samples to test both the wet-bench and bioinformatics/dry-bench aspects of the tests. Methods-based proficiency testing surveys are limited by the number and types of mutations that either are naturally present or can be introduced into a single DNA sample.

Objective: -To address these limitations by exploring a model of in silico proficiency testing in which sequence data from a single well-characterized specimen are manipulated electronically.

Design: -DNA from the College of American Pathologists reference genome was enriched using the Illumina TruSeq and Life Technologies AmpliSeq panels and sequenced on the MiSeq and Ion Torrent platforms, respectively. The resulting data were mutagenized in silico and 26 variants, including single-nucleotide variants, deletions, and dinucleotide substitutions, were added at variant allele fractions (VAFs) from 10% to 50%. Participating clinical laboratories downloaded these files and analyzed them using their clinical bioinformatics pipelines.

Results: -Laboratories using the AmpliSeq/Ion Torrent and/or the TruSeq/MiSeq participated in the 2 surveys. On average, laboratories identified 24.6 of 26 variants (95%) overall and 21.4 of 22 variants (97%) with VAFs greater than 15%. No false-positive calls were reported. The most frequently missed variants were single-nucleotide variants with VAFs less than 15%. Across both challenges, reported VAF concordance was excellent, with less than 1% median absolute difference between the simulated VAF and mean reported VAF.

Conclusions: -The results indicate that in silico proficiency testing is a feasible approach for methods-based proficiency testing, and demonstrate that the sensitivity and specificity of current next-generation sequencing bioinformatics across clinical laboratories are high.

Download full-text PDF

Source
http://dx.doi.org/10.5858/arpa.2016-0194-CPDOI Listing

Publication Analysis

Top Keywords

proficiency testing
28
silico proficiency
12
next-generation sequencing
12
methods-based proficiency
12
testing surveys
8
single-nucleotide variants
8
clinical laboratories
8
proficiency
7
testing
7
variants
6

Similar Publications

Quality Assurance (QA) plays a pivotal role in safeguarding the accuracy and reliability of laboratory test results, which are integral to informed clinical decision-making and optimal patient outcomes. External Quality Assessment (EQA), a cornerstone of QA, is mandated by international standards such as ISO/IEC 15189 to ensure laboratory competence and comparability across institutions. Despite India's position as the third-highest organ transplanting nation globally, a significant void persists in the availability of accredited EQA providers specialising in transplant immunology and immunophenotyping (IPT).

View Article and Find Full Text PDF

Introduction: Modern orthopaedic residency training increasingly integrates knowledge, skills, and behavior (KSB), in line with updated American Board of Orthopaedic Surgery (ABOS) and Accreditation Council for Graduate Medical Education (ACGME) guidelines. Developments in simulation technology-including high-fidelity simulators, virtual reality, and data-driven assessment tools-enable programs to target both technical and non-technical competencies. This paper examines how innovations in simulation, curriculum design, and performance assessment are shaping the future of orthopaedic education.

View Article and Find Full Text PDF

We present a novel computational model employing hierarchical active inference to simulate reading and eye movements. The model characterizes linguistic processing as inference over a hierarchical generative model, facilitating predictions and inferences at various levels of granularity, from syllables to sentences. Our approach combines the strengths of large language models for realistic textual predictions and active inference for guiding eye movements to informative textual information, enabling the testing of predictions.

View Article and Find Full Text PDF

Purpose: This study endeavors to conduct a comprehensive assessment on the performance of large language models (LLMs) in health consultation for individuals living with HIV, delve into their applicability across a diverse array of dimensions, and provide evidence-based support for clinical deployment.

Patients And Methods: A 23-question multi-dimensional HIV-specific question bank was developed, covering fundamental knowledge, diagnosis, treatment, prognosis, and case analysis. Four advanced LLMs-ChatGPT-4o, Copilot, Gemini, and Claude-were tested using a multi-dimensional evaluation system assessing medical accuracy, comprehensiveness, understandability, reliability, and humanistic care (which encompasses elements such as individual needs attention, emotional support, and ethical considerations).

View Article and Find Full Text PDF

Background: Children with hearing impairment (HI) are at risk for language difficulties, which can persist during childhood. There is a lack of clinical language tests adapted for young preschool children, enabling early identification of language delays. The expressive phonological test PEEPS-SE could enable such testing in these ages.

View Article and Find Full Text PDF