HiCNorm

Scripts to run HiCNorm

Usage

Rscript HiCNorm.R [options]

Options:

-i INPUT, --input=INPUT
	raw HiC matrix

-o OUTPUT, --output=OUTPUT
	normalized HiC matrix

-f GENOMIC_FEATURE, --genomic_feature=GENOMIC_FEATURE
	genomic feature file

-c COV, --cov=COV
	minimum coverage [default 1]

-l LEN, --len=LEN
	minimum effective fragment length fraction of the bin [default 0.1]

-s GC, --gc=GC
	minimum gc content [default 0.3]

-m MAP, --map=MAP
	minimum mappability [default 0.8]

-n, --negative_binomial
	use negative binomial regression

-h, --help
	Show this help message and exit

Input and Output Format

Input matrix file contains four columns: chromosome, first bin, second bin, and raw counts. Input genomic feature files contain six columns: chromosome, bin start position, bin end position, fragment length, GC content, and mappbility. Output matrix file cotains four columns: chromosome, first bin, second bin, and normalized counts.

Example

A demo data of chrmosome 19 form mESC HindIII HiC data is in the data folder. The data is from Fraser, J. et al. Molecular Systems Biology (2015).

Rscript HiCNorm.R -i data/mESC.HindIII.raw.chr19.txt -o data/mESC.HindIII.HiCNorm.chr19.txt -f data/F_GC_M_Hind3_50Kb_el.chr19.txt

Genomic Feature Files

Genomic feature files for GRCh38, hg19, mm10, and mm9 can be found at here.

Citation

If you use HiCNorm, please cite the following paper:

• Hu M, Deng K, Selvaraj S, Qin ZS, Ren B and Liu JS (2012) HiCNorm: removing biases in Hi-C data via Poisson regression. (2012) Bioinformatics 28 (23), 3131-3133.

Contact

For any questions or comments, please contact Ming Hu or Yunjiang Qiu.