Normalization of Chromosome Contact Maps: Matrix Balancing and Visualization

Autor: Romain Koszul, Pierrick Moreau, Axel Cournac, Shogofa Mortaza, Lyam Baudry, Cyril Matthey-Doret
Přispěvatelé: Régulation spatiale des Génomes - Spatial Regulation of Genomes, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Collège Doctoral, Sorbonne Université (SU), Laboratoire Cogitamus, Silvio Bicciato, Francesco Ferrari
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Hi-C Data Analysis : methods and protocols
Silvio Bicciato, Francesco Ferrari. Hi-C Data Analysis : methods and protocols, 2301, Springer US, pp.1-15, 2022, Methods in Molecular Biology, 978-1-0716-1390-0 (ebook). ⟨10.1007/978-1-0716-1390-0_1⟩
Methods in Molecular Biology ISBN: 9781071613894
Popis: International audience; Over the last decade, genomic proximity ligation approaches have reshaped our vision of chromosomes 3D organizations, from bacteria nucleoids to larger eukaryotic genomes. The different protocols (3Cseq, Hi-C, TCC, MicroC [XL], Hi-CO, etc.) rely on common steps (chemical fixation digestion, ligation…) to detect pairs of genomic positions in close proximity. The most common way to represent these data is a matrix, or contact map, which allows visualizing the different chromatin structures (compartments, loops, etc.) that can be associated to other signals such as transcription, protein occupancy, etc. as well as, in some instances, to biological functions.In this chapter we present and discuss the filtering of the events recovered in proximity ligation experiments as well as the application of the balancing normalization procedure on the resulting contact map. We also describe a computational tool for visualizing normalized contact data dubbed Scalogram.The different processes described here are illustrated and supported by the laboratory custom-made scripts pooled into "hicstuff," an open-access python package accessible on github ( https://github.com/koszullab/hicstuff ).
Databáze: OpenAIRE