GiniQC: a measure for quantifying noise in single-cell Hi-C data.

Bioinformatics

Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.

Published: May 2020

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 And Implementation: 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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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8453230PMC
http://dx.doi.org/10.1093/bioinformatics/btaa048DOI Listing

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