Sign in
BioinformaticsPLoS Computational Biology
Peer-reviewed journal article

qc3C: reference-free quality control for Hi-C sequencing data

Matthew Z. DeMaereiD, Aaron E. DarlingiD

Abstract

Hi-C is a sample preparation method that enables high-throughput sequencing to capture genome-wide spatial interactions between DNA molecules. The technique has been successfully applied to solve challenging problems such as 3D structural analysis of chromatin, scaffolding of large genome assemblies and more recently the accurate resolution of metagenome-assembled genomes (MAGs). Despite continued refinements, however, Hi-C library preparation remains a complex laboratory protocol and diligent quality management is recommended to avoid costly failure. Current wet-lab protocols for Hi-C library QC provide only a crude assay, while commonly used sequence-based QC methods demand a reference genome; the quality of which can skew results. We propose a new, reference-free approach for Hi-C library quality assessment that requires only a modest amount of sequencing data. The algorithm builds upon the observation that proximity ligation events are likely to create k -mers that would not naturally occur in the sample. Our software tool (qc3C) is to our knowledge the first to implement a reference-free Hi-C QC tool, and also provides reference-based QC, enabling Hi-C to be more easily applied to non-model organisms and environmental samples. We characterise the accuracy of the new algorithm on simulated and real datasets and compare it to reference-based methods.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
13
FWCI
0.71
Field percentile
top 35%

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
THISSauria '17Yardımcı '19Golloshi '18DeMaere '17Lazaris '17Kadota '20
72% semantic matchBioinformatics
Michael E.G. Sauria, James Taylor·bioRxiv·Nov 14, 2017· 40 citations