DOI: 10.1093/bioinformatics/btx843

,  

PMID: 29300845

Issn Print: 1367-4803

Publication Date: 2018/05/15


Print

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

Nilesh R Tawari; Justine Jia Wen Seow; Dharuman Perumal; Jack L Ow; Shimin Ang; Arun George Devasia; Pauline C Ng

+ Author Information

Author Information: Computational and Systems Biology, Genome Institute of Singapore, Genome, #02-01, Singapore 138672, Singapore

    loading  Checking for direct PDF access through Ovid

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.

Related Topics

    loading  Loading Related Articles