Literature DB >> 29300845

ChronQC: a quality control monitoring system for clinical next generation sequencing.

Nilesh R Tawari1, Justine Jia Wen Seow1, Dharuman Perumal1, Jack L Ow1, Shimin Ang1, Arun George Devasia1, Pauline C Ng1.   

Abstract

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.

Mesh:

Year:  2018        PMID: 29300845     DOI: 10.1093/bioinformatics/btx843

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  1 in total

1.  Novel bioinformatics quality control metric for next-generation sequencing experiments in the clinical context.

Authors:  Maxim Ivanov; Mikhail Ivanov; Artem Kasianov; Ekaterina Rozhavskaya; Sergey Musienko; Ancha Baranova; Vladislav Mileyko
Journal:  Nucleic Acids Res       Date:  2019-12-02       Impact factor: 16.971

  1 in total

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