MOTIVATION: Hi-C contact maps reflect the relative contact frequencies between pairs of genomic loci, quantified through deep sequencing. Differential analyses of these maps enable downstream biological interpretations. However, the multi-fractal nature of the chromatin polymer inside the cellular envelope results in contact frequency values spanning several orders of magnitude: contacts between loci pairs separated by large genomic distances are much sparser than closer pairs. The same is true for poorly covered regions, such as repeated sequences. Both distant and poorly covered regions translate into low signal-to-noise ratios. There is no clear consensus to address this limitation. RESULTS: We present Serpentine, a fast, flexible procedure operating on raw data, which considers the contacts in each region of a contact map. Binning is performed only when necessary on noisy regions, preserving informative ones. This results in high-quality, low-noise contact maps that can be conveniently visualized for rigorous comparative analyses. AVAILABILITY AND IMPLEMENTATION: Serpentine is available on the PyPI repository and https://github.com/koszullab/serpentine; documentation and tutorials are provided at https://serpentine.readthedocs.io/en/latest/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

UNLABELLED: Different experimental results suggest the presence of an interplay between global transcriptional regulation and chromosome spatial organization in bacteria. The identification and clear visualization of spatial clusters of contiguous genes targeted by specific DNA-binding proteins or sensitive to nucleoid perturbations can elucidate links between nucleoid structure and gene expression patterns. Similarly, statistical analysis to assess correlations between results from independent experiments can provide the integrated analysis needed in this line of research. NuST (Nucleoid Survey tools), based on the Escherichia coli genome, gives the non-expert the possibility to analyze the aggregation of genes or loci sets along the genome coordinate, at different scales of observation. It is useful to discover correlations between different sources of data (e.g. expression, binding or genomic data) and genome organization. A user can use it on datasets in the form of gene lists coming from his/her own experiments or bioinformatic analyses, but also make use of the internal database, which collects data from many published studies. AVAILABILITY AND IMPLEMENTATION: NuST is a web server (available at http://www.lgm.upmc.fr/nust/). The website is implemented in PHP, SQLite and Ajax, with all major browsers supported, while the core algorithms are optimized and implemented in C. NuST has an extensive help page and provides a direct visualization of results as well as different downloadable file formats. A template Perl code for automated access to the web server can be downloaded at http://www.lgm.upmc.fr/nust/downloads/, in order to allow the users to use NuST in systematic bioinformatic analyses.