Abstract The q –gram distance between two strings $$s,s^\prime$$ , introduced by Ukkonen in 1992, is an alignment-free string similarity measure which can be computed in linear time, as opposed to the quadratic time necessary for alignment/edit distance. It is based on the $$L_1$$ -distance, or Manhattan-distance, between the multiplicity vectors of fixed-length substrings (so-called q-grams or k-mers ), and has been successfully applied in diverse bioinformatics settings. In this paper, we introduce the threshold q-gram distance (T q D), a new distance measure which is similar to the q -gram distance but uses reduced information on the multiplicities of the q -grams. The new measure retains the linear time computation of the q -gram distance but requires significantly less space. Storage space and accuracy of the measure can be controlled via a user-defined threshold t , which sets a limit on the maximum value of the integers in the multiplicity vectors. In particular, for $$t=1$$ , the comparison is made only on the basis of the sets of uniquely occurring q -grams on the one hand, and of repeated q -grams, on the other. We tested the new distance measure, using the benchmarking tool AFproject of Zielezinski et al. [Genome Biology, 2019], on several real-life data sets for phylogenetic reconstruction and compared the results with those of other k -mer based distance measures. Our experiments show that the new measure T q D compares well to other non-alignment based measures regarding accuracy, while requiring substantially less memory than the classic q -gram distance.

Pangenomics was originally defined as the problem of comparing the composition of genes into gene families within a set of bacterial isolates belonging to the same species. The problem requires the calculation of sequence homology among such genes. When combined with metagenomics, namely for human microbiome composition analysis, gene-oriented pangenome detection becomes a promising method to decipher ecosystem functions and population-level evolution. Established computational tools are able to investigate the genetic content of isolates for which a complete genomic sequence is available. However, there is a plethora of incomplete genomes that are available on public resources, which only a few tools may analyze. Incomplete means that the process for reconstructing their genomic sequence is not complete, and only fragments of their sequence are currently available. However, the information contained in these fragments may play an essential role in the analyses. Here, we present PanDelos-frags, a computational tool which exploits and extends previous results in analyzing complete genomes. It provides a new methodology for inferring missing genetic information and thus for managing incomplete genomes. PanDelos-frags outperforms state-of-the-art approaches in reconstructing gene families in synthetic benchmarks and in a real use case of metagenomics. PanDelos-frags is publicly available at https://github.com/InfOmics/PanDelos-frags.

An immunological data-driven model is proposed, for age related changes in the network of relationships among cell quantities of eight peripheral B lymphocyte subpopulations, that is, cells exhibiting all combinations of three specific receptor clusters (CD27, CD23, CD5). The model is based on immunological data (quantities of cells exhibiting CD19, characterizing B lymphocytes) from about six thousands patients, having an age ranging between one day and ninety-five years, by means of a suitably combination of data analysis methods, such as piecewise linear regression models. With relaxed values for statistically significant models (coefficient p-values bounded by 0.05), we found a network holding for all ages, that likely represents the general assessment of adaptive immune system for healthy human beings. When statistical validation comes to be more restrictive, we found that some of these interactions are lost with aging, as widely observed in medical literature. Namely, interesting (inverse or directed) proportions are highlighted among mutual quantities of a partition of peripheral B lymphocytes.