An integrated, automated, flexible and user-friendly tool for quality control in clinical research. It supports three major NGS sequencing technologies including Illumina, 454 and Ion Torrent along with Sanger sequencing. ClinQC offers full flexibility, accuracy and reproducibility. All input parameters can be customized in the “ClinQCOptions” configuration file. It is a one-stop solution to run from raw sequence reads and trace files to high quality FASTQ files with Sanger quality encoding. This tool can be easily integrated in any downstream analysis pipeline for, e.g., mutation screening. In summary ClinQC can be used to analyze 1) Sanger and NGS data together, 2) all quality control parameters can be customized for different sequencing data, 3) thousands of datasets / patients / samples can be analyzed in a single run, 4) paired-end, single-end reads and mixed reads generated from Illumina, 454 and Ion Torrent can be analyzed simultaneously in a single run. ClinQC excels over existing tools and software for better usability, multiple data handling, Sanger sequencing data analysis and common input output model for Sanger and NGS data analysis.

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ClinQC classification

ClinQC specifications

Software type:
Pipeline
Restrictions to use:
None
Output data:
It returns a unified FASTQ files with Sanger (PHRED) quality encoding.
Operating system:
Unix/Linux
Parallelization:
CUDA
Computer skills:
Advanced
Stability:
Stable
Interface:
Command line interface
Input data:
ClinQC takes raw reads in any native file format of their sequencing platforms.
Biological technology:
Illumina, Life Technologies, Roche
Programming languages:
Python
License:
GNU Lesser General Public License version 3.0
Version:
1.0
Requirements:
Perl 5.12 or higher, Java 1.7 or higher

Publications

  • (Pandey et al., 2016) ClinQC: a tool for quality control and cleaning of Sanger and NGS data in clinical research. BMC bioinformatics.
    DOI: 10.1186/s12859-016-0915-y

ClinQC support

Maintainer

Credits

Institution(s)

Health & Environment Department, Molecular Diagnostics, AIT Austrian Institute of Technology GmbH, Vienna, Austria; Institut für Populationsgenetik, Vetmeduni Vienna, Vienna, Austria

Funding source(s)

This work was supported by the Austrian Institute of Technology (AIT).

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