Welcome to genereporter’s documentation!

genereporter is a Python library Sami developed as part of her Bachelor’s thesis.

genereporter can help researchers of any background quickly visualize and understand a gene of interest’s expression levels in their specific dataset.

Using scRNA-sequencing data (for now), genereporter generates automatic analysis reports and visualizations, granting wet-lab researchers access to output usually generated manually by computational researchers.

genereporter has three different modes of analysis:

• Cell type specific

• Gene regulatory network (GRN) specific

• Sample (patient) specific

genereporter is available to implement as a no-code front-end interface for wet-lab researchers, or as a Python library for bioinformaticians to integrate into their pipelines.

Check out the Usage section for further information.

Note

This is a work in progress. Feel free to open an issue on GitHub with any comments or questions.

• Usage
• Cell Pipeline API
• GRN Pipeline API
• Sample Pipeline API
• Using CellPipeline
• Using GRNPipeline
• Using SamplePipeline
• SCENIC Pipeline