In:
Bioinformatics, Oxford University Press (OUP), Vol. 36, No. 9 ( 2020-05-01), p. 2902-2904
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
1367-4803
,
1367-4811
DOI:
10.1093/bioinformatics/btaa048
Language:
English
Publisher:
Oxford University Press (OUP)
Publication Date:
2020
detail.hit.zdb_id:
1468345-3
SSG:
12
