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About libraries in a Data Cruncher analysis

At the moment, Data Cruncher offers a set of predefined libraries curated by Seven Bridges bioinformaticians, which are automatically available every time an analysis is started. The list of available libraries depends on the editor you are using (JupyterLab or RStudio).

JupyterLab

The libraries are installed using conda, as JupyterLab supports multiple programming languages and conda is a language-agnostic package manager.

Here is a list of libraries that are installed by default:

  • Python2 \ Python3:
    • path.py, biopython, pymongo, cytoolz, pysam, pyvcf, ipywidgets, beautifulsoup4, sevenbridges-python, cigar, bioservices, intervaltree, appdirs, cssselect, bokeh, scikit-allel, cairo, lxml, cairosvg, rpy2
  • R:
    • r-ggfortify, r, r-stringi, r-pheatmap, r-gplots, bioconductor-ballgown, bioconductor-deseq2, bioconductor-metagenomeseq, bioconductor-biomformat, bioconductor-biocinstaller, sevenbridges-r, r-xml

The aforementioned libraries are installed on top of the libraries that are already available in datascience-notebook.

You can also install libraries directly from the notebook and use them during the execution of your analysis. For optimal performance and avoidance of potential conflicts, we recommend using conda when installing libraries within your analyses. However, unlike default libraries, libraries installed in that way will not be automatically available next time the analysis is started.

RStudio (beta)

RStudio installation is based on the rstudio/verse image from The Rocker Project and contains tidyverse, devtools, tex and publishing-related packages. For more information about the image, please see its Docker Hub repository.

Here is a list of libraries that are installed by default:

  • CRAN - BiocManager, ggfortify, pheatmap, gplots
  • Bioconductor - ballgown, DESeq2, metagenomeSeq, biomformat, BiocInstaller
  • sevenbridges-r

Updated 9 months ago

About libraries in a Data Cruncher analysis


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