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Tool for identifying transposon insertions in Insertional Mutagenesis screens from gene-transposon fusions using single- and paired-end RNA-sequencing data.

Project description

IM-Fusion

IM-Fusion is a tool for identifying transposon insertion sites in insertional mutagenesis screens using single- and paired-end RNA-sequencing data. It essentially identifies insertion sites from gene-transposon fusions in the RNA-sequencing data, which represent splicing events between the transposon and endogeneous genes.

IM-Fusion also identifies candidate genes for a given screen using a statistical test (based on the Poisson distribution) that identifies Commonly Targeted Genes (CTGs) – genes that are more frequently affected by insertions than would be expected by chance. To further narrow down a list of CTGs, which may contain hundreds of genes, IM-Fusion also tests if insertions in a CTG have a significant effect on the expression of the gene, which is a strong indicator of them having an actual biological effect.

IM-Fusion has the following key features:

  • It identifies transposon insertion sites from both single- and paired-end RNA-sequencing data, without having any special sequencing requirements.
  • It uses a gene-centric approach – both for the identification of insertions and for testing of differential expression for identified candidate genes – which greatly reduces the number of false positive candidate genes.
  • It implements several exon-level and gene-level differential expression tests, which provide detailed insight into the effects of insertions on the expression of their target gene(s). By providing both a group-wise and a single-sample version of the test, IM-Fusion can identify effects for a single insertion in a specific sample, or determine the general effect of insertions on a given gene within the tumor cohort.

For more details on the approach and a comparison with existing methods, please see our manuscript.

Documentation

IM-Fusion’s documentation is available at nki-ccb.github.io/imfusion.

References

de Ruiter J.R., Kas S.M. et al. “Identifying transposon insertions and their effects from RNA-sequencing data” Nucleic Acids Research 2017, in press.

License

This software is released under the MIT license.

History

0.3.2 (2017-05-11)

  • Properly added star-fusion support to star aligner (was previously not fully merged).
  • Changed documentation URLs to new repository.

0.3.1 (2017-05-09)

  • Several small fixes for Python 2.7 compatibility.
  • Fixed issue in CTG test that occurs when no insertions are within the gene windows.
  • Replaced usage of deprecated .ix indexer for pandas DataFrames.
  • Updated documentation.

0.3.0 (2017-05-04)

  • Refactored external tools into the imfusion.external module.
  • Use docker/tox for testing against multiple Python versions locally.
  • Added additional checks for inputs and improved error messages.
  • Added support for DataFrame insertion inputs to DE testing functions.
  • Added building of exon gtf as part of imfusion-build.
  • Added identification of endogenous fusions using STAR-Fusion as part of imfusion-insertions (using STAR). Also adds script for building (murine) STAR-Fusion references.
  • Made matplotlib/seaborn lazy imports that are only required when actually using the plotting functions. This makes IM-Fusion easier to use on headless servers/HPCs.

0.2.0 (2017-03-09)

  • Added support for the STAR aligner.
  • Added detection of novel transcripts using StringTie.
  • Changed reference building to generate a self-contained reference.
  • Refactored differential expression tests + added gene-level test.

0.1.0 (2016-03-26)

  • First release on GitHub.

Project details


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