doc: add a section on general tools used for Hi-C

principles.qmd

@@ -418,3 +418,58 @@ fs::dir_tree('HiCool/')
 All the files generated by a single `HiCool` pipeline execution contain the same 6-letter unique hash to make sure they are not overwritten if re-executing the same command. 
 :::
 
+## Exploratory data analysis of processed Hi-C files
+
+Once Hi-C raw data has been transformed into a set of processed files, 
+exploratory data analysis is typically conducted following two main routes: 
+
+- Data visualization; 
+- Data investigation.
+
+During the last decade, a number of softwares have been developed
+to unlock **Hi-C data visualization and investigation**. Here we provide a non-exhaustive
+list of notable tools developed throughout the recent years for downstream Hi-C analysis, 
+selected from [this longer list](https://github.com/mdozmorov/HiC_tools). 
+
+* 2012-2015: 
+
+  - HiTC (2012)
+  - HiCCUPS (2014) 
+  - HiCseg (2014) 
+  - Fit-Hi-C (2014) 
+  - HiC-Pro (2015) 
+  - diffHic (2015)
+  - cooltools (2015) 
+  - HiCUP (2015)
+  - HiCPlotter (2015)
+  - HiFive (2015)
+
+* 2016-2019: 
+
+  - CHiCAGO (2016)
+  - TADbit (2017)
+  - HiCRep (2017)
+  - HiC-DC (2017)
+  - GoTHIC (2017)
+  - HiCExplorer (2018)
+  - Boost-HiC (2018)
+  - HiCcompare (2018)
+  - HiPiler (2018)
+  - coolpuppy (2019)
+
+* 2020-present: 
+
+  - Serpentine (2020)
+  - CHESS (2020)
+  - DeepHiC (2020)
+  - Chromosight (2020)
+  - Mustache (2020)
+  - TADcompare (2020)
+  - POSSUM (2021)
+  - Calder (2021)
+  - HICDCPlus (2021)
+  - plotgardener (2021)
+  - GENOVA (2021)
+
+All references as well as many other softwares and references are available 
+[here](https://github.com/mdozmorov/HiC_tools).