How to cite the Bioconductor package ideal

Marini, F., Linke, J., & Binder, H. (2020). ideal: an R/Bioconductor package for Interactive Differential Expression Analysis. bioRxiv. https://doi.org/10.1101/2020.01.10.901652

1.

Marini F, Linke J, Binder H. ideal: an R/Bioconductor package for Interactive Differential Expression Analysis [Internet]. bioRxiv; 2020. Available from: http://dx.doi.org/10.1101/2020.01.10.901652

@UNPUBLISHED{Marini2020-hb,
  title       = "ideal: an {R/Bioconductor} package for Interactive
                 Differential Expression Analysis",
  author      = "Marini, Federico and Linke, Jan and Binder, Harald",
  abstract    = "AbstractBackgroundRNA sequencing (RNA-seq) is an ever
                 increasingly popular tool for transcriptome profiling. A key
                 point to make the best use of the available data is to provide
                 software tools that are easy to use but still provide
                 flexibility and transparency in the adopted methods. Despite
                 the availability of many packages focused on detecting
                 differential expression, a method to streamline this type of
                 bioinformatics analysis in a comprehensive, accessible, and
                 reproducible way is lacking.ResultsWe developed the ideal
                 software package, which serves as a web application for
                 interactive and reproducible RNA-seq analysis, while producing
                 a wealth of visualizations to facilitate data interpretation.
                 ideal is implemented in R using the Shiny framework, and is
                 fully integrated with the existing core structures of the
                 Bioconductor project. Users can perform the essential steps of
                 the differential expression analysis work-flow in an assisted
                 way, and generate a broad spectrum of publication-ready
                 outputs, including diagnostic and summary visualizations in
                 each module, all the way down to functional analysis. ideal
                 also offers the possibility to seamlessly generate a full HTML
                 report for storing and sharing results together with code for
                 reproducibility.Conclusionideal is distributed as an R package
                 in the Bioconductor project
                 (http://bioconductor.org/packages/ideal/), and provides a
                 solution for performing interactive and reproducible analyses
                 of summarized RNA-seq expression data, empowering researchers
                 with many different profiles (life scientists, clinicians, but
                 also experienced bioinformaticians) to make the ideal use of
                 the data at hand.",
  institution = "bioRxiv",
  month       =  jan,
  year        =  2020,
  url         = "http://dx.doi.org/10.1101/2020.01.10.901652",
  doi         = "10.1101/2020.01.10.901652"
}

TY  - INPR
AU  - Marini, Federico
AU  - Linke, Jan
AU  - Binder, Harald
TI  - ideal: an R/Bioconductor package for Interactive Differential Expression
      Analysis
PY  - 2020
DA  - 2020/1/11
AB  - AbstractBackgroundRNA sequencing (RNA-seq) is an ever increasingly popular
      tool for transcriptome profiling. A key point to make the best use of the
      available data is to provide software tools that are easy to use but still
      provide flexibility and transparency in the adopted methods. Despite the
      availability of many packages focused on detecting differential
      expression, a method to streamline this type of bioinformatics analysis in
      a comprehensive, accessible, and reproducible way is lacking.ResultsWe
      developed the ideal software package, which serves as a web application
      for interactive and reproducible RNA-seq analysis, while producing a
      wealth of visualizations to facilitate data interpretation. ideal is
      implemented in R using the Shiny framework, and is fully integrated with
      the existing core structures of the Bioconductor project. Users can
      perform the essential steps of the differential expression analysis
      work-flow in an assisted way, and generate a broad spectrum of
      publication-ready outputs, including diagnostic and summary visualizations
      in each module, all the way down to functional analysis. ideal also offers
      the possibility to seamlessly generate a full HTML report for storing and
      sharing results together with code for reproducibility.Conclusionideal is
      distributed as an R package in the Bioconductor project
      (http://bioconductor.org/packages/ideal/), and provides a solution for
      performing interactive and reproducible analyses of summarized RNA-seq
      expression data, empowering researchers with many different profiles (life
      scientists, clinicians, but also experienced bioinformaticians) to make
      the ideal use of the data at hand.
DO  - 10.1101/2020.01.10.901652
UR  - http://dx.doi.org/10.1101/2020.01.10.901652
ER  -