GOTHiC, a probabilistic model to resolve complex biases and to identify real interactions in Hi-C data
Fig 4
Comparison of mouse the fetal liver Hi-C data after processing by hiclib, hicpipe and GOTHiC.
(A-B) Contact maps of mouse Chromosome 10 containing relative probability computed by hiclib and observed/expected log ratio obtained with hicpipe respectively resulting from Hi-C experiment (left panel) and random ligation experiment (right panel) in fetal liver. The intensity of the signal is summarized by the gradient above each contact map. (C) Influence of the relative coverage on the distribution of number of observed interactions (top panel), hiclib and hicpipe interaction ranking (middle and bottom panels), in the HiC (left) and random ligation (right) samples. The ranked lists were divided into quartiles, the first quartiles correspond to the top ranked interactions. The distribution of the number of reads per interaction is represented in the top panel with green box plots (corresponding y-axis is placed on the right of the plot). (D) Recovery of 80,085 highest ranked intearctions in hicpipe and hiclib by GOTHiC.