This tool allows a quick comparison between multiple Hi-C matrices of the Hi-C counts enrichment at different genomic ranges / distances up to whole chromosomes. Biological replicates should display the exact same distribution while samples coming from different cell-lines, treated versus untreated samples or mutant versus wild-type samples can display a different distribution at long and/or close ranges.
The results of this tool usually reflect the proportion of long-range and short-range contacts calculated in each sample by hicQC. Local TAD or contact enrichments will not impact the results computed by this tool, hicPCA is better suited for that purpose.
hicPlotDistVsCounts should be used on corrected matrices with large bins (e.g. at least 50kb bins), otherwise the curves will be very spiky and unstable at longer ranges because of the sparseness of the contacts. The tool hicMergeMatrixBins can be used to merge matrix bins and the tool hicCorrectMatrix can be used for matrix correction before using hicPlotDistVsCounts.
hicPlotDistVsCounts -m \
condition1_sample1_50_bins_merged.h5 \
condition1_sampel2_50_bins_merged.h5 \
condition2_sample1_50_bins_merged.h5 \
condition2_sample2_50_bins_merged.h5 \
-o counts_vs_dist_50_bins_merged.png \
--labels 'Cond 1 Sample 1' 'Cond 1 Sample 2' 'Cond 2 Sample 1' 'Cond 2 Sample 2' \
--maxdepth 20000000 \
--plotsize 5 4.2
Here, we see that the samples of the first condition are not so well correlated, but they follow the same tendencies and are distinct from the two samples of the second condition. The later are well correlated and display enriched long-range contacts compared to the samples of the first condition.