Hi-C is a powerful experimental method to probe DNA-DNA long-range interactions on the whole genome [Lieberman-Aiden2009].
We developed a novel computational method using a balanced non-negative matrix factorization (BNMF) that can flexibly identify small clusters of spatially proximal genomic regions based on Hi-C contact maps.
Here, we give examples on how to use our tool.
The environmental requirement is:
Or, you can use the free installer provided by Anaconda to avoid any configuration issue.
Download the bnmf package that contains source codes and data.
Uncompress it and you will see
contact_map.py-- source code for BNMF
yeast_chr_len.txt-- chromosome lengths for the yeast genome
hg18_chr_len.txt-- chromosome lengths for the human genome using hg18 reference
HindIII_intersect_EcoRI_fdr0.01_inter.txt-- yeast inter-chromosome interactions [Duan2010]
HindIII_intersect_EcoRI_fdr0.01_intra.txt-- yeast intra-chromosome interactions [Duan2010]
origins_nonCDR_early.txt-- yeast early origin sites [Duan2010]
IMR90.uij.chr22-- human intra-chromosome interaction matrix at 40k resolution [Dixon2012]
IMR90.domain.txt-- topological domains defined for IMR90 cell line [Dixon2012]
*.ipynb-- the raw files used to generate this tutorial
*.html-- ipython notebook files transformed into html format
Then, let's go through following examples:
If you have any problem on this tutorial or our paper, please contact the authors.