Kuijjer Lab

Tools

Network tools

  • PyPanda: a Python package for gene regulatory network reconstruction using PANDA (Passing Attributes between Networks for Data Assimilation). The original version of PyPanda is available here (by David van IJzendoorn). An updated version is available on here (by Alessandro Marin)
  • PUMA: PANDA Using MicroRNA Associations. PUMA is an extension of PANDA that can include miRNAs are regulators in the regulatory network model. C++ and MATLAB versions are available on Github. A Python version of PUMA is available on here (by Alessandro Marin)
  • LIONESS: Linear Interpolation to Obtain Network Estimates for Single Samples. LIONESS is an equation that can be used together with network reconstruction algorithms to extract networks for individual samples. An R package that can be used as a wrapper around unipartite or bipartite network reconstruction functions and that contains an example differential co-expression analysis is available at Github
  • netZoo: the network zoo package integrates several network methods, including PANDA (Kimberly Glass), LIONESS, CONDOR (John Platig), and ALPACA (Megha Padi), in one pipeline. It is available here (by Tian Wang)

Other tools

  • SAMBAR: Subtyping Agglomerated Mutations Using Annotation Relations. SAMBAR de-sparsifies somatic mutation data into pathway mutation scores, and clusters the data into subtypes using binomial distance. An R package is available on Github
  • YARN: Yet Another RNA-Seq package (by Joe Paulson). YARN offers robust multi-tissue RNA-Seq preprocessing and normalization and is available on Bioconductor

Resources

  • We post many of our resources on the Kuijjer Lab's Zenodo data page, including:
    • Gene regulatory networks for 38 human tissues, modeled with PANDA
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    • miRNA gene regulatory networks for 38 human tissues, modeled with PUMA
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    • Gene and pathway mutation scores for 5,805 primary tumors, calculated using SAMBAR
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  • Single-sample networks for 9,435 samples derived from 38 GTEx tissues are available on the Glass Lab page