3. Calculate 1D metrics for comparison of two samples

3.1 Quick start

h1d two ISC ./test_data/GSE104334_Rad21KD.chr21.matrix.gz \
	./test_data/GSE104334_Ctrl.chr21.matrix.gz \
	50000 chr21 -o treat_vs_control_ISC

This command would generate a bedGraph file (treat_vs_control_ISC.bedGraph) for ISC. An example result can be checked from here

3.2 Usage

The analysis of two-sample metrics cound be run by h1d two sub-command :

$ h1d two -h # type -h for help
usage: __main__.py two [-h] [-p PARAMETER] [-o OUTNAME] [-d] [-s START]
                       [-e END] [--datatype DATATYPE] [--gt GT]
                       type matrix controlmatrix resolution chromosome

1D metrics designed for comparison of two Hi-C samples

positional arguments:
  type                  Type of 1D metrics for two-sample comparison,should be
                        one of {ISC,CIC,SSC,deltaDLR,CD,IESC,IASC,IFC,DRF}
  matrix                Path of treated file (matrix or rawhic).
  controlmatrix         Path of control file (matrix or rawhic).
  resolution            Resolution of input matrix
  chromosome            Chromosome number ('chr21',i.e).

optional arguments:
  -h, --help            show this help message and exit
  -p PARAMETER, --parameter PARAMETER
                        Parameter for indicated metrics
  -o OUTNAME, --outname OUTNAME
                        output name (default: metricsChange)
  -d, --draw            Plot figure for candidate region
  -s START, --start START
                        Start sites for plotting
  -e END, --end END     End sites for plotting
  --datatype DATATYPE   matrix or rawhic
  --gt GT               genome table file

  • type : type of 1D metrics could be one of {ISC,CIC,SSC,deltaDLR,CD,IESC,IASC,IFC,DRF}:

    • Insulation Score Change (ISC) (PMID: 31495782)

    • Contrast Index Change(CIC)

    • Separation Score Change(SSC)

    • Delta Distal-to-Local Ratio (deltaDLR) (PMID: 30146161)

    • Correlation Difference (CD) (PMID: 20513432)

    • IntraScore Change(IASC)

    • InterScore Change (IESC)

    • Interaction Frequency Change (IFC)

    • Directional Relative Frequency (DRF)(Original metric)

    Details is shown in our paper: link in the future

  • -p or --parameter for each metrics:

Type Description default value
ISC square size 300000
CIC length of bins 300000
SSC length of bins 300000
deltaDLR Local distance 3000000
CD Correlation method pearson
IASC Paramter for TAD calling 300000
IESC Paramter for TAD calling 300000
IFC FDR threshold 0.05
DRF length of bins 200000-5000000

3.3 Calculate 1D metrics (two-sample)

  • Use contact matrix:

    h1d two ISC ./test_data/GSE104334_Rad21KD.chr21.matrix.gz \
	./test_data/GSE104334_Ctrl.chr21.matrix.gz 50000 chr21 \
	--datatype matrix -p 300000 -o treat_vs_control_ISC

  • Use raw hic:

    h1d two ISC ./test_data/GSE104334_Rad21KD.hic \
	./test_data/GSE104334_Ctrl.hic 50000 chr21 \
	--datatype rawhic --gt ./test_data/hg19_genome_table.txt \
	-p 300000 -o treat_vs_control_ISC

  • Use cool file

    h1d two ISC ./test_data/GSE104334_Rad21KD.50000.cool \
	./test_data/GSE104334_Ctrl.50000.cool 50000 chr21 \
	--datatype cool --gt ./test_data/hg19_genome_table.txt \
	-p 300000 -o treat_vs_control_ISC

3.3.1 Multiprocessing for all chromomes:

  • chromosome , set chromosome to “all” will compute metrics for all chromosomes.

  • data, if calculating for all chromosomes, the input file should be absolute folder of contact matrix.

  • -maxchr, Maximum index of chromosome (human genome is 22,i.e.). It will compute chromosome 1~maxchr plus chromosome X.

  • --prefix, the prefix of matrix file, please modify the name of zipped matrix to ${prefix}chr1.matrix.gz. If you used our dump function, the file should be:

    ├── observed.KR.chr1.matrix.gz
├── observed.KR.chr10.matrix.gz
├── observed.KR.chr11.matrix.gz
├── observed.KR.chr12.matrix.gz
├── observed.KR.chr13.matrix.gz
├── observed.KR.chr14.matrix.gz

    so the prefix is observed.KR.

  • -n, Number of processors

To run all chromosomes parallel (treat vs control), do:

h1d one ISC ./test/Treat/ ./test/Control/  50000 all 
	--maxchr 22 --prefix observed.KR. -n 30 -o treat_vs_control

Output would be treat_vs_control_IS_allchr.csv.

3.4 Visualize 1D metrics (two-sample)

  • Use contact matrix:

    h1d two CIC ./test_data/GSE104334_Rad21KD.chr21.matrix.gz \
	./test_data/GSE104334_Ctrl.chr21.matrix.gz 50000 chr21 \
    --datatype matrix -p 300000 -o treat_vs_control_ISC \
	--draw -s 26000000 -e 33000000

  • Use raw .hic file

    h1d two CIC ./test_data/GSE104334_Rad21KD.hic \
	./test_data/GSE104334_Ctrl.hic 50000 chr21 \
	--datatype rawhic --gt ./test_data/hg19_genome_table.txt \
	-p 300000 -o treat_vs_control_ISC \
	--draw -s 26000000 -e 33000000

  • Use .cool file

    h1d two CIC ./test_data/GSE104334_Rad21KD.50000.cool \
	./test_data/GSE104334_Ctrl.50000.cool 50000 chr21 \
	--datatype cool --gt ./test_data/hg19_genome_table.txt \
	-p 300000 -o treat_vs_control_ISC \
	--draw -s 26000000 -e 33000000
RTDimport