2020/10/04 by Nelle Varoquaux, Virginia S. Lioy, Varoquaux, Nelle +5
Biochemistry, Genetics and Molecular Biology · Environmental Science · #Bacterial Genetics and Biotechnology #Bacteriophages and microbial interactions #FOS: Biological sciences #Genomics (q-bio.GN) #Genomics and Phylogenetic Studies
paper · pdf · doi:10.48550/arxiv.2010.01718
openalex publication_date 2020/10/04 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Just as in eukaryotes, high-throughput chromosome conformation capture (Hi-C)\ndata have revealed nested organizations of bacterial chromosomes into\noverlapping interaction domains. In this chapter, we present a multiscale\nanalysis framework aiming at capturing and quantifying these properties. These\ninclude both standard tools (e.g. contact laws) and novel ones such as an index\nthat allows identifying loci involved in domain formation independently of the\nstructuring scale at play. Our objective is two-fold. On the one hand, we aim\nat providing a full, understandable Python/Jupyter-based code which can be used\nby both computer scientists as well as biologists with no advanced\ncomputational background. On the other hand, we discuss statistical issues\ninherent to Hi-C data analysis, focusing more particularly on how to properly\nassess the statistical significance of results. As a pedagogical example, we\nanalyze data produced in it Pseudomonas aeruginosa, a model pathogenetic\nbacterium. All files (codes and input data) can be found on a github\nrepository. We have also embedded the files into a Binder package so that the\nfull analysis can be run on any machine through internet.\n