RESUMO
Summary: ChronQC is a quality control (QC) tracking system for clinical implementation of next-generation sequencing (NGS). ChronQC generates time series plots for various QC metrics to allow comparison of current runs to historical runs. ChronQC has multiple features for tracking QC data including Westgard rules for clinical validity, laboratory-defined thresholds and historical observations within a specified time period. Users can record their notes and corrective actions directly onto the plots for long-term recordkeeping. ChronQC facilitates regular monitoring of clinical NGS to enable adherence to high quality clinical standards. Availability and implementation: ChronQC is freely available on GitHub (https://github.com/nilesh-tawari/ChronQC), Docker (https://hub.docker.com/r/nileshtawari/chronqc/) and the Python Package Index. ChronQC is implemented in Python and runs on all common operating systems (Windows, Linux and Mac OS X). Contact: tawari.nilesh@gmail.com or pauline.c.ng@gmail.com. Supplementary information: Supplementary data are available at Bioinformatics online.
Assuntos
Sequenciamento de Nucleotídeos em Larga Escala , Controle de Qualidade , Confiabilidade dos Dados , Sequenciamento de Nucleotídeos em Larga Escala/métodos , SoftwareRESUMO
Targeted next-generation sequencing is becoming increasingly common as a clinical diagnostic and prognostic test for patient- and tumor-specific genetic profiles as well as to optimally select targeted therapies. Here, we describe a custom-developed, next-generation sequencing test for detecting single-nucleotide variants (SNVs) and short insertions and deletions (indels) in 93 genes related to gastrointestinal cancer from routine formalin-fixed, paraffin-embedded clinical specimens. We implemented a validation strategy, based on the College of American Pathologists requirements, using reference DNA mixtures from cell lines with known genetic variants, which model a broad range of allele frequencies. Test sensitivity achieved >99% for both SNVs and indels, with allele frequencies >10%, with high specificity (97.4% for SNVs and 93.6% for indels). We further confirmed test accuracies using primary formalin-fixed, paraffin-embedded colorectal cancer specimens characterized by alternative and conventional clinical diagnostic technologies. Robust performance was observed on the formalin-fixed, paraffin-embedded specimens: sensitivity was 97.2% and specificity was 99.2%. We also observed high intrarun and inter-run reproducibility, as well as a low cross-contamination rate. Overall assessment using cell line samples and formalin-fixed, paraffin-embedded samples showed that our custom next-generation sequencing assay has consistent detection sensitivity down to 10% variant frequency.