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Pairsqc

Codacy Badge

  • Pairsqc is a tool for generating a QC report for a Hi-C pairs file.
  • Version history

Dependency

  • Python >=2.7

  • R

  • Python packages

    • pypairix
    pip install pypairix
    
  • R packages

    • devtools
    R CMD Install devtools
    
    • Nozzle
    # open an R session and type in the following.
    install.packages( "Nozzle.R1", type="source" );

    If the above didn't work, try the following.

    # Install as follows, outside the pairsqc directory (avoid git clone inside another git repo)
    git clone https://github.com/parklab/nozzle
    cd nozzle
    ./install.sh
    
    • Plotosaurus
    # open an R session and type in the following.
    library(devtools)
    install_url("https://github.com/SooLee/plotosaurus/archive/0.9.2.zip")

Installation

# no need to install, just download
git clone https://github.com/4dn-dcic/pairsqc

Usage

  1. pairsqc.py
usage: pairsqc.py [-h] [-p PAIRS] [-c CHRSIZE] [-t INPUT_TYPE]
                  [-O OUTDIR_PREFIX] [-s SAMPLE_NAME]

QC for Pairs

optional arguments:
  -h, --help            show this help message and exit
  -p PAIRS, --pairs PAIRS
                        input pairs file
  -c CHRSIZE, --chrsize CHRSIZE
                        input chromsize file
  -t INPUT_TYPE, --input_type INPUT_TYPE
                        input file type (P:pairs, M:merged_nodups,
                        OM:old_merged_nodups)
  -O OUTDIR_PREFIX, --outdir_prefix OUTDIR_PREFIX
                        prefix of output directory (output directory name will
                        be <outdir_prefix>_report
  -s SAMPLE_NAME, --sample_name SAMPLE_NAME
                        sample name to be used as the file prefix and in the
                        report (do not include space)
  -M MAX_LOGDISTANCE, --max_logdistance MAX_LOGDISTANCE
                        Maximum log distance. This number should not be larger
                        than all chromosomes. Choose 8.2 for mouse/chicken, 7.9 for zebrafish. Default
                        8.4 (human).
  1. plot.r
Rscript plot.r <enzyme_type> [<report_dir>]
# <enzyme_type> is either 4 (four-cutter, MboI, DpnII) or 6 (six-cutter, HindIII, NcoI). This value is used to draw a line for expected convergence point for read orientations.
# If <report_dir> is not specified, it assumed './report' as the report directory. The output directory of pairsqc.py must match <report_dir>, which is '<OUTPUT_PREFIX>_report'.

Output

If output prefix is not specified, the output directory will be './report' The python script generates two text output files, report/$sample_name.cis_to_trans.out and report/$sample_name.plot_table.out. The R script generates image files in report/plots. The output report can be found in report/pairsqc_report.html. (example : https://s3.amazonaws.com/4dn-github-related-files/pairsqc/test_report_d3_v4/pairsqc_report.html (multi-sample) )

  • Output text file example : cis_to_trans.out plot_table.out

  • Note: To view the d3 plots in the output html, the file must be on a webserver. Try the following if you want to see it locally.

python -m http.server 8066
# then open localhost:8066 on a browser, select your html file.

Example run

python pairsqc.py -p test_samples/merged_nodup.tab.chrblock_sorted.txt.gz -c test_samples/GRCh37.chrom.sizes.mainonly.female -t M
Rscript plot.r 4
zip report.zip report # if you want to create a zip file for the report.

Max log distance

The default max logdistance is set to be 8.4, which works for human. For non-human species, use -M option to reset the max logdistance. (e.g. -M 8.2 for mouse, -M 7.9 for zebrafish) The value for human was calculated as below:

  • The largest chromosome for human (hg38) is 248,956,422 bp. log10(248956422) = 8.396123. The value must be larger than this number but doesn't have to be much larger.

 

QC metrics and plots

Cis-to-trans ratio

  • Cis-to-trans ratio is computed as number_of_cis_reads / (number_of_cis_reads + number_of_trans_reads) * 100, where a cis read is defined as an intrachromosomal read whose 5'-5' separation is > T. A trans read is an interchromosomal read. T=20kb.
  • Cis-to-trans ratio at T=5kb and T=20kb show only minor difference (less than 10%).

Percent long-range intrachromosome reads

  • This is number_of_long_cis_reads / total_reads, whereas a long_cis_read is defined as an intrachromosomal read whose 5'-5' separation is > T. T=20kb. This is identical to the 'cis_read' in the cis-to-trans ratio, since cis-to-trans ratio is computed using only long-range cis reads. Rao et al. suggests 15% is the minimal allowed value and 40% or higher suggests a good library.

Proportion of read orientations versus genomic separation

  • s = 5'-5' separation of an intrachromosomal read.
  • s is binned at log10 scale at interval of 0.1 (growing by ~1.25-fold).
  • For each bin, the number of reads with each of the four orientations is obtained. To compute proportion, each count is supplemented with a pseudocount of 1E-100, and divided by the sum over the four orientations for that bin.
  • The first bin where the four orientations converge is called resolution, and is determined by using standard deviation of the proportions < 0.005.
  • The contact frequency vs genomic separation plot is similar to Proportion of read orientation versus genomic separation, except the actual read counts are displayed instead of proportions.

Contact propability versus genomic separation

  • s = 5'-5' separation of an intrachromosomal read.
  • s is binned at log10 scale at interval of 0.1 (growing by ~1.25-fold).
  • For each bin, contact probability is computed as number_of_reads / number_of_possible_reads / bin_size.
    • number_of_possible_reads is computed as the sum of L_chr - s_mid - 1 over all chromosomes included in the input chrsize file, where L_chr is the length of a chromosome. This is equivalent of L_genome - N_chr * (s_mid + 1), where L_genome is the sum of all chromosome lengths and N_chr is the number of chromosomes. S_mid is the mid point of the bin at log10 scale (bin 10^2.8 ~ 10^2.9 has mid point 10^2.85).
    • bin_size is computed as max distance - min distance (e.g. for bin 10^2.8 ~ 10^ 2.9, the binsize is 10^2.9 - 10^2.8).
  • Slope of the region 10^4 ~ 10^5.5 is displayed.

Contact propability versus genomic separation, per chromosome

  • Same as Contact propability versus genomic separation, but for each chromosome

Speed

12 sec/M reads on Macbook Air with 2.2 GHz Intel Core i7. (~3.5 hrs for 1B reads)