Sign in
BioinformaticsbioRxiv
Preprint

FreeHi-C: high fidelity Hi-C data simulation for benchmarking and data augmentation

Ye ZhengiD, Sündüz KeleşiD

Abstract

Ability to simulate realistic high-throughput chromatin conformation (Hi-C) data is foundational for developing and benchmarking statistical and computational methods for Hi-C data analysis. We propose FreeHi-C, a data-driven Hi-C simulator for simulating and augmenting Hi-C datasets. FreeHi-C employs a non-parametric strategy for estimating interaction distribution of genome fragments from a given sample and simulates Hi-C reads from interacting fragments. Data from FreeHi-C exhibit higher fidelity to the biological Hi-C data compared with other tools in its class. FreeHi-C not only enables benchmarking a wide range of Hi-C analysis methods but also boosts the precision and power of differential chromatin interaction detection methods while preserving false discovery rate control through data augmentation.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISHong '20Ardakany '19Shaked '25Dimmick '20Cameron '20Lazaris '17
69% semantic matchBioinformatics
Hao Hong, Shuai Jiang, Hao Li+12 more·PLoS Computational Biology·Feb 21, 2020· 96 citations