GiniQC

GiniQC is a quality control tool to assess the quality of single-cell Hi-C (scHi-C) data, a technique pivotal for understanding the variability in chromatin structure and dynamics at the single-cell level. Given the high degree of noise characteristic of current scHi-C protocols, GiniQC addresses a critical need for precise data quality evaluation to ensure the reliability of biological interpretations drawn from scHi-C analyses.

GiniQC quantifies the uneven distribution of inter-chromosomal reads within the scHi-C contact matrix, indicating the level of noise in the data. Through practical examples, GiniQC has demonstrated its effectiveness in complementing existing quality control measures for scHi-C data, providing researchers with a more comprehensive assessment of data quality. Additionally, GiniQC offers insights into how various data processing steps affect the quality of scHi-C data, aiding in optimizing data analysis workflows.

Topic

Data quality management;Bioinformatics;DNA

Detail

  • Operation: Validation;Standardisation and normalisation

  • Software interface: Command-line tool,Script

  • Language: Python, shell

  • License: GNU Lesser General Public License v3.0

  • Cost: -

  • Version name: -

  • Credit: National Institutes of Health, Harvard College Research Program, Pechet Family Research Fund.

  • Input: -

  • Output: -

  • Contact: Peter J Park peter_park@hms.harvard.edu

  • Collection: -

  • Maturity: -

Publications

  • GiniQC: a measure for quantifying noise in single-cell Hi-C data.
  • Horton CA, et al. GiniQC: a measure for quantifying noise in single-cell Hi-C data. GiniQC: a measure for quantifying noise in single-cell Hi-C data. 2020; 36:2902-2904. doi: 10.1093/bioinformatics/btaa048
  • https://doi.org/10.1093/BIOINFORMATICS/BTAA048
  • PMID: 32003786
  • PMC: PMC8453230

Download and documentation

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