iCount-Mini 3.0.1

Computational pipeline for analysis of iCLIP data

iCount-Mini

This is a fork of iCount maintained by members of Jernej Ule's group, focussing on the peak calling features of iCount.

Run commands using: iCount-Mini <command>

Note on small differences of terminology between iCount-Mini and iCount

• In iCount-Mini, sigxls = iCount peaks and iCount-Mini peaks = iCount clusters. This is to bring the terminology more in line with the rest of the field.
• In iCount-Mini RNA-maps have been renamed to 'metagene', to distinguish these plots which include only CLIP data from other RNA-maps which group crosslinks into categories dependent on orthogonal data, such as alternatively spliced exons.

iCount: protein-RNA interaction analysis

iCount is a Python module and associated command-line interface (CLI), which provides all the commands needed to process iCLIP data on protein-RNA interactions and generate:

• demultiplexed and adapter-trimmed FASTQ files
• BAM files with mapped iCLIP reads
• identified protein-RNA cross-linked sites, saved to BED files
• statistically significant cross-linked sites, saved to BED files
• peaks of significant cross-linked sites, saved to BED files
• grouping of individual replicate experiments
• metagene generation showing the positional distribution of cross-linked sites relative to genomic landmarks
• kmer enrichment analysis

You may start with the tutorial or dive into the documentation.

iCount-Mini Authors

iCount-Mini is maintained by members of Jernej Ule's group.

iCount Authors

iCount is developed and supported by Tomaž Curk from the Bioinformatics Laboratory at the University of Ljubljana, Faculty of Computer and Information Science and in collaboration with the laboratory of Jernej Ule.

The development started in late 2008 when Tomaž Curk and Gregor Rot wrote a first prototype of iCount. In mid-2016, Jure Zmrzlikar from Genialis helped refactoring and improving the code, which is now available here.

Development

To install a development version of iCount-Mini, use this command. It's recommended to do this within a Python virtual environment.

pip install --upgrade -r requirements-rtd.txt -e .