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mQC : a post-mapping data exploration tool for ribosome profiling

Steven Verbruggen (UGent) and Gerben Menschaert (UGent)
(2018) COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. 181.
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Abstract
Background and objective: Ribosome profiling is a recent next generation sequencing technique enabling the genome-wide study of gene expression in biomedical research at the translation level. Too often, researchers precipitously start trying to test their hypotheses after alignment of their data, without checking the quality and the general features of their mapped data. Despite the fact that these checks are essential to prevent errors and ensure valid conclusions afterwards, easy-to-use tools for visualizing the quality and overall outlook of mapped ribosome profiling data are lacking. Methods: We present mQC, a modular tool implemented as a Bioconda package and also available in the Galaxy tool shed. Herewith both bio-informaticians as well as non-experts can easily perform the indispensable visualization of both the quality and the general features of their mapped P-site corrected ribosome profiling reads. The user manual, the raw code and more information can be found on its GitHub repository (https://github.com/Biobix/mQC). Results: mQC was tested on multiple datasets to assess its general applicability and was compared to other tools that partly perform similar tasks. Conclusions: Our results demonstrate that mQC can accomplish an unfilled but essential position in the ribosome profiling data analysis procedure by performing a thorough RIBO-Seq-specific exploration of aligned and P-site corrected ribosome profiling data.
Keywords
Ribosome profiling, NGS, Quality visualization, Triplet periodicity, QUALITY-CONTROL, IN-VIVO, TRANSLATION, REPRODUCIBILITY, IMPACT

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MLA
Verbruggen, Steven, and Gerben Menschaert. “MQC : A Post-Mapping Data Exploration Tool for Ribosome Profiling.” COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, vol. 181, 2018, doi:10.1016/j.cmpb.2018.10.018.
APA
Verbruggen, S., & Menschaert, G. (2018). mQC : a post-mapping data exploration tool for ribosome profiling. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 181. https://doi.org/10.1016/j.cmpb.2018.10.018
Chicago author-date
Verbruggen, Steven, and Gerben Menschaert. 2018. “MQC : A Post-Mapping Data Exploration Tool for Ribosome Profiling.” COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 181. https://doi.org/10.1016/j.cmpb.2018.10.018.
Chicago author-date (all authors)
Verbruggen, Steven, and Gerben Menschaert. 2018. “MQC : A Post-Mapping Data Exploration Tool for Ribosome Profiling.” COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 181. doi:10.1016/j.cmpb.2018.10.018.
Vancouver
1.
Verbruggen S, Menschaert G. mQC : a post-mapping data exploration tool for ribosome profiling. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE. 2018;181.
IEEE
[1]
S. Verbruggen and G. Menschaert, “mQC : a post-mapping data exploration tool for ribosome profiling,” COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, vol. 181, 2018.
@article{8641318,
  abstract     = {{Background and objective: Ribosome profiling is a recent next generation sequencing technique enabling the genome-wide study of gene expression in biomedical research at the translation level. Too often, researchers precipitously start trying to test their hypotheses after alignment of their data, without checking the quality and the general features of their mapped data. Despite the fact that these checks are essential to prevent errors and ensure valid conclusions afterwards, easy-to-use tools for visualizing the quality and overall outlook of mapped ribosome profiling data are lacking. 
Methods: We present mQC, a modular tool implemented as a Bioconda package and also available in the Galaxy tool shed. Herewith both bio-informaticians as well as non-experts can easily perform the indispensable visualization of both the quality and the general features of their mapped P-site corrected ribosome profiling reads. The user manual, the raw code and more information can be found on its GitHub repository (https://github.com/Biobix/mQC). 
Results: mQC was tested on multiple datasets to assess its general applicability and was compared to other tools that partly perform similar tasks. 
Conclusions: Our results demonstrate that mQC can accomplish an unfilled but essential position in the ribosome profiling data analysis procedure by performing a thorough RIBO-Seq-specific exploration of aligned and P-site corrected ribosome profiling data.}},
  articleno    = {{104806}},
  author       = {{Verbruggen, Steven and Menschaert, Gerben}},
  issn         = {{0169-2607}},
  journal      = {{COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE}},
  keywords     = {{Ribosome profiling,NGS,Quality visualization,Triplet periodicity,QUALITY-CONTROL,IN-VIVO,TRANSLATION,REPRODUCIBILITY,IMPACT}},
  language     = {{eng}},
  pages        = {{7}},
  title        = {{mQC : a post-mapping data exploration tool for ribosome profiling}},
  url          = {{http://doi.org/10.1016/j.cmpb.2018.10.018}},
  volume       = {{181}},
  year         = {{2018}},
}
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