akagi

Name is derived from my favourite anime character but if you really want some meaning in this acronym, it can stand for Archaeal (proKAryotic) Genomic Instruments. Or something else.

DISCLAIMER

As one can notice from the package name, it is suitable for prokaryotes. Eukaryotic data processing is still WIP and, frankly, I don't know if I really need to implement this modules because there is no urge for that.

Brief introduction

This Python package simplifies work with Hi-C data by providing numerous useful functions for:

• launching the most popular pipelines to get contact matrices from raw Hi-C reads
• parsing data after calculations are finished (descriptive statistics, contact matrices, etc)
• exploratory data analysis and visualization

Structure

For now, akagi consists of three main parts:

1. pipelines contains scripts for launching popular Hi-C pipelines: juicer, distiller and HiC-Pro. This module is run from the command line.
2. afterwork launches tools for downstream analysis such as compartmentalization analysis, TAD and loop calling, RedC signal annotation. This module is run from the command line.
3. imagineer plots the data in suitable format. This module was designed to be used in Jupyter Notebook.