Title |
ChronQC: a quality control monitoring system for clinical next generation sequencing
|
---|---|
Published in |
Bioinformatics, December 2017
|
DOI | 10.1093/bioinformatics/btx843 |
Pubmed ID | |
Authors |
Nilesh R Tawari, Justine Jia Wen Seow, Dharuman Perumal, Jack L Ow, Shimin Ang, Arun George Devasia, Pauline C Ng |
Abstract |
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. 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). [email protected] or [email protected]. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 3 | 30% |
United States | 3 | 30% |
Italy | 1 | 10% |
Canada | 1 | 10% |
Norway | 1 | 10% |
Unknown | 1 | 10% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 7 | 70% |
Scientists | 3 | 30% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 19 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 5 | 26% |
Other | 4 | 21% |
Student > Ph. D. Student | 3 | 16% |
Student > Bachelor | 1 | 5% |
Professor | 1 | 5% |
Other | 2 | 11% |
Unknown | 3 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 5 | 26% |
Computer Science | 4 | 21% |
Agricultural and Biological Sciences | 4 | 21% |
Medicine and Dentistry | 1 | 5% |
Unknown | 5 | 26% |