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      FQC Dashboard: integrates FastQC results into a web-based, interactive, and extensible FASTQ quality control tool

      other
      1 , 2 , 1
      Bioinformatics
      Oxford University Press

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          Abstract

          Summary

          FQC is software that facilitates quality control of FASTQ files by carrying out a QC protocol using FastQC, parsing results, and aggregating quality metrics into an interactive dashboard designed to richly summarize individual sequencing runs. The dashboard groups samples in dropdowns for navigation among the data sets, utilizes human-readable configuration files to manipulate the pages and tabs, and is extensible with CSV data.

          Availability and implementation

          FQC is implemented in Python 3 and Javascript, and is maintained under an MIT license. Documentation and source code is available at: https://github.com/pnnl/fqc.

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          Author and article information

          Journal
          Bioinformatics
          Bioinformatics
          bioinformatics
          Bioinformatics
          Oxford University Press
          1367-4803
          1367-4811
          01 October 2017
          09 June 2017
          09 June 2017
          : 33
          : 19
          : 3137-3139
          Affiliations
          [1 ]Earth and Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA and
          [2 ]Computation and Analytics Division, Pacific Northwest National Laboratory, Richland, WA 99352, USA
          Author notes
          [* ]To whom correspondence should be addressed.

          Associate Editor: Jonathan Wren

          Article
          btx373
          10.1093/bioinformatics/btx373
          5870778
          28605449
          d996cdb1-4ed7-4dfe-b54e-91c046c60a11
          © The Author 2017. Published by Oxford University Press.

          This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

          History
          : 09 March 2017
          : 28 April 2017
          : 06 June 2017
          Page count
          Pages: 3
          Funding
          Funded by: DOE 10.13039/100000015
          Award ID: DE-AC06-76RL01830
          Categories
          Applications Notes
          Data and Text Mining

          Bioinformatics & Computational biology
          Bioinformatics & Computational biology

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