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Abstract

Summary

Single-cell Hi-C (scHi-C) allows the study of cell-to-cell variability in chromatin structure and dynamics. However, the high level of noise inherent in current scHi-C protocols necessitates careful assessment of data quality before biological conclusions can be drawn. Here we present GiniQC, which quantifies unevenness in the distribution of inter-chromosomal reads in the scHi-C contact matrix to measure the level of noise. Our examples show the utility of GiniQC in assessing the quality of scHi-C data as a complement to existing quality control measures. We also demonstrate how GiniQC can help inform the impact of various data processing steps on data quality.

Availability

Source code and documentation are freely available at https://github.com/4dn-dcic/GiniQC

Supplementary information

Supplementary data are available at Bioinformatics online.

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Author notes

Present address: Department of Genetics, Stanford University, 291 Campus Drive, Stanford, CA
© The Author(s) (2020). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
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Associate Editor:
Alfonso Valencia
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Alfonso Valencia
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  • Supplementary data

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