Elon MaskED

Elongated Mask-based Enrichment Detector.

Elon MaskED is an instrument for searching elongated loops on HiC contact maps. It uses mask and Spearman correlation to filtetr out significant and elongated loops in specific direction.

What is elongated loops?

Chromatin loops represent contacts between distant gene loci e.g. enhancers and promoters ¹. They are usually represented on HiC contact maps as symmetrical points of high intensity, showing an increased frequency of contacts between regions. A more detailed analysis of HiC maps and an increase in resolution loops with an asymmetrical shape were revaled, which elongated along the axis of the matrix. Noteworthy, that elongated loops are observed in the genomes of various set of eukaryotes indicating that their shape may be link to a different mechanism of formation and/or biological function rather than symmetric loops.

Installation and usage

Elon MaskED can be used in notebook-like format. Command-line API implementation is in progress now. It will be soon)

Clone repo to your local machine using SSH:

git@github.com:anshtompel/Elon-MaskED.git

or HTTPS

https://github.com/anshtompel/Elon-MaskED.git

and and go to the directory:

cd Elon-Masked

Use Elon MaskED in Jupyter notebook or in IDE would you like to use:

from elon import elon_call
elon_call(your arguments)

Elon MaskED pipeline

Elon MaskED searches for loops in several stages:

• Filter pixels using fit to Weibull distribution (inspired by LASCA²)
• Cluster sugnificant pixels and detect potential loops
• Create elongated mask from pileup of "mix" loops
• Count Spearman correlation between selected loops and maks

Tool output

Elon MaskED outputs a .bedpe file with genome coordinates of detected loops and figures of detected loops pileups created with Coolpuppy package in .png format.

.bedpe file represents bed-like data format which contains the coordinates of the "window" in the center of which the detected loop is located

Examples of output pileup:

Citation

Footnotes

1. Herrmann J. C., Beagrie R. A., Hughes J. R. Making connections: enhancers in cellular differentiation // Trends in Genetics. - 2022. - V. 38, N. 4 - P. 395–408. DOI: 10.1016/j.tig.2021.10.008 ↩

2. Luzhin, A. V., Golov, A. K., Gavrilov, A. A., Velichko, A. K., Ulianov, S. V., Razin, S. V., & Kantidze, O. L. (2021). LASCA: loop and significant contact annotation pipeline. Scientific reports, 11(1), 6361. DOI 10.1038/s41598-021-85970-4 ↩