5e412867b72db8c2e65c2c090dc0682d257fa737 jnavarr5 Tue Jun 10 16:15:24 2025 -0700 Adding an anchor for the Data Access section, refs #35861 diff --git src/hg/makeDb/trackDb/human/hg38/hicAndMicroC.html src/hg/makeDb/trackDb/human/hg38/hicAndMicroC.html index 48475356783..9774fa9baa9 100644 --- src/hg/makeDb/trackDb/human/hg38/hicAndMicroC.html +++ src/hg/makeDb/trackDb/human/hg38/hicAndMicroC.html @@ -1,148 +1,149 @@
Square mode provides a traditional Hi-C display in which chromosome positions are mapped along the top-left-to-bottom-right diagonal, and interaction values are plotted on both sides of that diagonal to form a square. The upper-left corner of the square corresponds to the left-most position of the window in view, while the bottom-right corner corresponds to the right-most position of the window.
The color shade at any point within the square shows the proximity score for two genomic regions: the region where a vertical line drawn from that point intersects with the diagonal, and the region where a horizontal line from that point intersects with the diagonal. A point directly on the diagonal shows the score for how proximal a region is to itself (scores on the diagonal are usually quite high unless no data are available). A point at the extreme bottom left of the square shows the score for how proximal the left-most position within the window is to the right-most position within the window.
In triangle mode, the display is quite similar to square except that only the top half of the square is drawn (eliminating the redundancy), and the image is rotated so that the diagonal of the square now lies on the horizontal axis. This display consumes less vertical space in the image, although it may be more difficult to ascertain exactly which positions correspond to a point within the triangle.
In arc mode, simple arcs are drawn between the centers of interacting regions. The color of each arc corresponds to the proximity score. Self-interactions are not displayed.
There are four score values available in this display: NONE, VC, VC_SQRT, and KR. NONE provides raw, un-normalized counts for the number of interactions between regions. VC, or Vanilla Coverage, normalization (Lieberman-Aiden et al., 2009) and the VC_SQRT variant normalize these count values based on the overall count values for each of the two interacting regions. Knight-Ruiz, or KR, matrix balancing (Knight and Ruiz, 2013) provides an alternative normalization method where the row and column sums of the contact matrix equal 1.
Color intensity in the heatmap goes up to indicate higher scores, but eventually saturates at a maximum beyond which all scores share the same color intensity. The value of this maximum score for saturation can be set manually by un-checking the "Auto-scale" box. When the "Auto-scale" box is checked, it automatically sets the saturation maximum to be double (2x) the median score in the current display window.
The first protocol, in situ Hi-C, was published in 2014 as a technique for obtaining full-genome proximity data while keeping the cell nucleus intact (Rao et al., 2014). This method uses a restriction enzyme to cleave DNA before linking. The second protocol, Micro-C XL, is an update to the Micro-C method of obtaining chromatin conformation data (Hsieh et al., 2016, Hsieh et al., 2015), and has largely supplanted the original. Both the original Micro-C and the updated version are variants of Hi-C chromatin conformation capture that use micrococcal nuclease to segment the genome before linking. This results in data sets with resolution down to the nucleosome level. The original Micro-C method had difficulty recovering higher order interactions, and the updated protocol makes use of additional cross-linking chemicals to address that issue.
We downloaded the .hic contact matrix files with the following accessions from the 4D Nucleome Data Portal: 4DNFI18Q799K, 4DNFI2TK7L2F, 4DNFIFLJLIS5, and 4DNFIQYQWPF5. The files are parsed for display using the Straw library from the Aiden lab at Baylor College of Medicine.
Knight P, Ruiz D. A fast algorithm for matrix balancing. IMA J Numer Anal. 2013 Jul;33(3):1029-1047.
Krietenstein N, Abraham S, Venev SV, Abdennur N, Gibcus J, Hsieh TS, Parsi KM, Yang L, Maehr R, Mirny LA et al. Ultrastructural Details of Mammalian Chromosome Architecture. Mol Cell. 2020 May 7;78(3):554-565.e7. PMID: 32213324
Lieberman-Aiden E, van Berkum NL, Williams L, Imakaev M, Ragoczy T, Telling A, Amit I, Lajoie BR, Sabo PJ, Dorschner MO et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science. 2009 Oct 9;326(5950):289-93. PMID: 19815776; PMC: PMC2858594
Rao SS, Huntley MH, Durand NC, Stamenova EK, Bochkov ID, Robinson JT, Sanborn AL, Machol I, Omer AD, Lander ES et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell. 2014 Dec 18;159(7):1665-80. PMID: 25497547; PMC: PMC5635824