Data processing articles from across Nature Portfolio

Here, the authors present RecombinHunt, a computational method based on big data analysis, that enhances community-based detection of recombinant viral lineages.

Multi-Attribute Subset Selection is an algorithm for identifying the most descriptive growth conditions in microbial phenotyping experiments. This streamlines high-throughput phenotyping efforts and helps to reveal biological insights.

Mutational signatures help to deconvolve the different processes that shape cancer genomes. A new tool now alleviates some of the persistent challenges in the field.

Selecting omic biomarkers using both their effect size and their differential status significance (i.e., selecting the “volcano-plot outer spray”) has long been equally biologically relevant and statistically troublesome. However, recent proposals are paving the way to resolving this dilemma.

Reconstructing phylogenetic trees from large collections of genome sequences is a computationally challenging task. We developed MAPLE, a method for performing phylogenetic inference on large numbers of closely related genomes, which might be useful when studying the evolution and spread of SARS-CoV-2 and of infectious pathogens in future pandemics.