*`*allValidPairs` - combined valid pairs from all read chunks
*`*allValidPairs` - combined valid pairs from all read chunks
*`*mergestat` - statistics about duplicates removal and valid pairs information
*`*mergestat` - statistics about duplicates removal and valid pairs information
...
@@ -137,19 +149,21 @@ Finaly, an important metric is to look at the fraction of intra and
...
@@ -137,19 +149,21 @@ Finaly, an important metric is to look at the fraction of intra and
inter-chromosomal interactions, as well as long range (>20kb) versus short
inter-chromosomal interactions, as well as long range (>20kb) versus short
range (<20kb) intra-chromosomal interactions.
range (<20kb) intra-chromosomal interactions.
## Contact maps
### Contact maps
Intra et inter-chromosomal contact maps are build for all specified resolutions.
Intra et inter-chromosomal contact maps are build for all specified resolutions.
The genome is splitted into bins of equal size. Each valid interaction is
The genome is splitted into bins of equal size. Each valid interaction is
associated with the genomic bins to generate the raw maps.
associated with the genomic bins to generate the raw maps.
In addition, Hi-C data can contain several sources of biases which has to be
In addition, Hi-C data can contain several sources of biases which has to be
corrected.
corrected.
The current workflow uses the [ìced](https://github.com/hiclib/iced) and
The HiC-Pro workflow uses the [ìced](https://github.com/hiclib/iced) and
[Varoquaux and Servant, 2018](http://joss.theoj.org/papers/10.21105/joss.01286)
[Varoquaux and Servant, 2018](http://joss.theoj.org/papers/10.21105/joss.01286)
python package which proposes a fast implementation of the original ICE
python package which proposes a fast implementation of the original ICE
normalization algorithm (Imakaev et al. 2012), making the assumption of equal
normalization algorithm (Imakaev et al. 2012), making the assumption of equal
visibility of each fragment.
visibility of each fragment.
**Output directory: `results/hicpro/matrix`**
*`*.matrix` - genome-wide contact maps
*`*.matrix` - genome-wide contact maps
*`*_iced.matrix` - genome-wide iced contact maps
*`*_iced.matrix` - genome-wide iced contact maps
...
@@ -176,6 +190,54 @@ files.
...
@@ -176,6 +190,54 @@ files.
This format is memory efficient, and is compatible with several software for
This format is memory efficient, and is compatible with several software for
downstream analysis.
downstream analysis.
## Contact maps
Contact maps are usually stored as simple txt (`HiC-Pro` based), .hic (`Juicer/Juicebox` based) and .(m)cool (`cooler/Higlass` based) formats.
Note that .cool and .hic format are compressed and usually much more efficient that the txt format.
In the current workflow, we propose to use the `cooler` format as a standard after valid pairs detection as it is the input of several downstream analysis tools.
Raw contact maps are therefore stored in *results/contact_maps/raw* which contains the different maps in txt and cool format, at various resolutions.
Normalized contact maps are stored in *results/contact_maps/norm* which contains the different maps in txt, cool, and mcool format.
Note that txt contact maps generated with `cooler` are identical to those generated by `HiC-Pro`.
However, differences can be observed on the normalized contact maps as the balancing algorithm is not the same.
## Downstream analysis
Downstream analysis are performed from cool files at specified resolution.
### Distance decay
The distance decay plot shows the relationship between contact frequencies and genomic distance. It gives a good indication of the compaction of the genome.
According to the organism, the slope of the curve should fit the expection of polymer physics models.
The results generated with the `HiCExplorer hicPlotDistVsCounts` tool are available in the *results/dist_decay/* folder.
### Compartments calling
Compartments calling is one of the most common analysis using Hi-C data which allow to detect A (open, active) / B (close, inactive) compartments.
In the first studies on the subject, the compartments were called at high/medium resolution (1000000 to 250000) which is enough to call A/B comparments.
Analysis at higher resolution have shown that these two main types of compartments can be further divided in more precise compartments subtypes.
Although different methods have been proposed for compartment calling, the standard remains the one based on eigen vector decomposition generation from the normalized correlation maps.
Here, we use the implementation available in the [`cooltools`](https://cooltools.readthedocs.io/en/lates) package.
Results are available in *results/compartments/* folder and includes :
*`*cis.vecs.tsv`: eigenvectors decomposition along the genome
*`*cis.lam.txt`: eigenvalues associated with the eigenvectors
### TADs calling
TADs has been described as functional units of the genome.
While contacts between genes and regulatority elements can occur within a single TADs, contacts between TADs are much less frequent, mainly due to the presence of insulation protein (such as CTCF) at their boundaries. Looking at Hi-C maps, TADs look like triangles around the diagonal. According to the contact map resolutions, TADs appear as hierarchical structures with a median size around 1Mb (in mammals), as well as smaller structures usually called sub-TADs of smaller size.
TADs calling remains a challenging task, and even if many methods have been proposed in the last decade, little overlap have been found between their results.
Currently, the pipeline proposes two approaches :
- Insulation score using the [`cooltools`](https://cooltools.readthedocs.io/en/latest/cli.html#cooltools-diamond-insulation) package. Results are availabe in *results/tads/insulation*.
-[`HiCExplorer TADs calling`](https://hicexplorer.readthedocs.io/en/latest/content/tools/hicFindTADs.html). Results are available at *results/tads/hicexplorer*.
Usually, TADs results are presented as simple BED files, or bigWig files, with the position of boundaries along the genome.
## MultiQC
## MultiQC
[MultiQC](http://multiqc.info) is a visualisation tool that generates a single
[MultiQC](http://multiqc.info) is a visualisation tool that generates a single
