What is Bacon?

Bacon is a comprehensive benchmark framework, which integrated 8 experimental datasets and 2 simulated datasets to perform testing, in addition, the high confident long-range interactions from ENCODE (1), the genetic interactions validated by eQTLs (2-3) and CISPR/dCas-9 (4) are gathered as gold standard loop sets to perform evaluation. Bacon also provides practical recommendations for users working with HiChIP (5) and/or ChIA-PET (6) analysis.

Schema of Bacon

Why do we need Bacon?

It is a great challenge to interpret the targeted conformation capture data (ChIA-PET and HiChIP) quantitatively, owing to the high prevalence of sequenced ligation junctions formed from non-meaningful close-range contacts. Therefore, we need to rely on the robust and efficient computational methods to remove the biases and more accurately quantify chromatin contacts. With these in mind, Bacon was developed to deepen the interpretation of targeted conformation data, and expedite the development of computational methods.

How to use Bacon?

1. Achieve experimental/simulation/gold standard Datasets.
2. Try different Tools with curated command line.
3. Evaluate the performance by Bacon pipeline.
4. Check the Recommendations for choosing proper tools.


1. The ENCODE Project Consortium. 2012. An integrated encyclopedia of DNA elements in the human genome. Nature 489: 57.

2. Consortium TG, Lappalainen T, Sammeth M, Friedländer MR, Hoen PAC ‘t, Monlong J, Rivas MA, Gonzàlez-Porta M, Kurbatova N, Griebel T, et al. 2013. Transcriptome and genome sequencing uncovers functional variation in humans. Nature 501: 506–511.

3. Aguet F, Brown A, Castel SE, Davis JR, He Y, Jo B, Mohammadi P, Park Y, Parsana P, Segrè AV, et al. 2017. Genetic effects on gene expression across human tissues. Nature 550: 204–213.

4. Gasperini M, Hill AJ, McFaline-Figueroa JL, Martin B, Kim S, Zhang MD, Jackson D, Leith A, Schreiber J, Noble WS, et al. 2019. A Genome-wide Framework for Mapping Gene Regulation via Cellular Genetic Screens. Cell 176: 377-390.e19.

5. Mumbach MR, Rubin AJ, Flynn RA, Dai C, Khavari PA, Greenleaf WJ, Chang HY. 2016. HiChIP: efficient and sensitive analysis of protein-directed genome architecture. Nat Methods 13: 919–922.

6. Fullwood MJ, Liu MH, Pan YF, Liu J, Xu H, Mohamed YB, Orlov YL, Velkov S, Ho A, Mei PH, et al. 2009. An oestrogen-receptor-α-bound human chromatin interactome. Nature 462: 58.

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