Software for "Sim3C: simulation of Hi-C and Meta3C proximity ligation sequencing technologies"

Dataset type: Software, Epigenomic
Data released on October 24, 2017

DeMaere MZ; Darling AE (2017): Software for "Sim3C: simulation of Hi-C and Meta3C proximity ligation sequencing technologies" GigaScience Database. http://dx.doi.org/10.5524/100368

DOI10.5524/100368

Chromosome conformation capture (3C) and HiC DNA sequencing methods have rapidly advanced our understanding of the spatial organization of genomes and metagenomes. Many variants of these protocols have been developed, each with their own strengths. Currently there is no systematic means for simulating sequence data from this family of sequencing protocols.
We describe a computational simulator that, given reference genome sequences and some basic parameters, will simulate HiC sequencing on those sequences. The simulator models the basic spatial structure in genomes that is commonly observed in HiC and 3C datasets, including the distance-decay relationship in proximity ligation, differences in the frequency of interaction within and across chromosomes, and the structure imposed by cells. A means to model the 3D structure of topologically associating domains (TADs) is provided. The simulator also models several sources of error common to 3C and HiC library preparation and sequencing methods, including spurious proximity ligation events and sequencing error.
We have introduced the first comprehensive simulator for 3C and HiC sequencing protocols. We expect the simulator to have use in testing of HiC data analysis algorithms, as well as more general value for experimental design, where questions such as the required depth of sequencing, enzyme choice, and other decisions must be made in advance in order to ensure adequate statistical power to test the relevant hypotheses.

Additional details

Read the peer-reviewed publication(s):

(PubMed: 29149264)

Additional information:

https://github.com/cerebis/sim3C

Accessions (data referenced by this study):

SRA: SRX377733
SRA: SRX527868
SRA: SRX263925
doi: 10.5061/dryad.gv595





File NameSample IDData TypeFile FormatSizeRelease Date 
ReadmeTEXT1.96 KB2017-10-24
GitHub archiveUNKNOWN1.5 MB2017-10-24
Displaying 1-2 of 2 File(s).
Funding body Awardee Award ID Comments
Australian Research Council SP Djordjevic LP150100912 Discovery Projects
Date Action
October 24, 2017 Dataset publish
January 9, 2018 Manuscript Link added : 10.1093/gigascience/gix103
November 9, 2022 Manuscript Link updated : 10.1093/gigascience/gix103