Nicola De Maio

Phylogeny-aided detection of contamination in nearly 5 million SARS-CoV-2 genomes

The paper develops PhyCD to detect contamination in SARS-CoV-2 genomes, identifying 10,942 putative contamination events across nearly 5 million genomes.

Modeling Site-Specific Mutation Patterns in Pandemic-Scale Phylogenetics

This paper introduces a site-specific mutation model (SSM) for pandemic-scale phylogenetics, showing it better captures mutation patterns in SARS-CoV-2 genomes than classical models.

CMAPLE 2: Fast and Accurate Phylogenetic Inference for Millions of Pathogen Genomes

CMAPLE 2 improves phylogenetic inference speed and memory efficiency for large pathogen genome datasets, enabling analysis of nearly four million SARS-CoV-2 genomes in 12 days.

Horse, not zebra: accounting for lineage abundance in maximum likelihood phylogenetics

The paper improves phylogenetic inference by incorporating lineage abundance into maximum likelihood methods, showing significant accuracy gains in SARS-CoV-2 data.

Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny

The paper reprocesses SARS-CoV-2 genomic data to correct systematic errors in phylogenies using a novel assembly tool, resulting in a cleaner global tree of 4.47 million samples.

Rate variation and recurrent sequence errors in pandemic-scale phylogenetics

The paper improves pandemic-scale phylogenetic analysis by addressing mutation rate variation and sequence errors, reconstructing a reliable phylogenetic tree of over 2 million SARS-CoV-2 genomes.

Highly recurrent multi-nucleotide mutations in SARS-CoV-2

The paper identifies highly recurrent multi-nucleotide mutations in SARS-CoV-2 and shows they are linked to transcription regulatory sequences, affecting computational evolutionary biology analyses.

Detecting interspecific positive selection using convolutional neural networks

This paper introduces a convolutional neural network to detect interspecific positive selection, achieving higher accuracy and robustness to alignment errors compared to traditional statistical methods.

This is SPRTA: assessing phylogenetic confidence at pandemic scales

SPRTA assesses phylogenetic confidence by evaluating evolutionary histories rather than clades, applied to a global SARS-CoV-2 dataset.

CMAPLE: efficient phylogenetic inference in the pandemic era

The paper introduces CMAPLE, an optimized phylogenetic inference method, and integrates it into IQ-TREE 2 for improved pandemic-scale genomic analysis.

SARS-CoV-2 lineage assignments using phylogenetic placement/UShER are superior to pangoLEARN machine learning method

This study compares pangoLEARN and pUShER for SARS-CoV-2 lineage assignment, finding pUShER more stable and accurate across pangolin versions.

Maximum likelihood pandemic-scale phylogenetics

The paper introduces MAPLE, a new phylogenetic analysis method that scales to large datasets by improving computational efficiency, outperforming existing tools like FastTree and RAxML-NG.

Dynamic, adaptive sampling during nanopore sequencing using Bayesian experimental design

This paper introduces BOSS-RUNS, a framework for dynamic nanopore sequencing that adapts in real-time to maximize information gain and reduce coverage bias.

SWAMPy: Simulating SARS-CoV-2 Wastewater Amplicon Metagenomes with Python

SWAMPy generates realistic SARS-CoV-2 wastewater amplicon metagenomes to test and improve analysis methods.

phastSim: efficient simulation of sequence evolution for pandemic-scale datasets

The paper introduces phastSim, a tool for efficiently simulating sequence evolution on large phylogenetic trees, particularly for SARS-CoV-2-like datasets.

Online Phylogenetics using Parsimony Produces Slightly Better Trees and is Dramatically More Efficient for Large SARS-CoV-2 Phylogenies than de novo and Maximum-Likelihood Approaches

This study compares online and de novo phylogenetic methods for SARS-CoV-2, finding that maximum parsimony online approaches are more accurate and efficient than maximum likelihood or de novo methods.

A daily-updated database and tools for comprehensive SARS-CoV-2 mutation-annotated trees

The paper introduces a daily-updated database of SARS-CoV-2 mutation-annotated trees and associated tools for querying and manipulating the data.

Phylogenetic Novelty Scores: a New Approach for Weighting Genetic Sequences

The paper introduces phylogenetic novelty scores to weight genetic sequences based on their evolutionary novelty, improving accuracy in character frequency estimation and other applications.

Ultrafast Sample Placement on Existing Trees (UShER) Empowers Real-Time Phylogenetics for the SARS-CoV-2 Pandemic

The paper introduces UShER, a method for ultrafast phylogenetic placement of SARS-CoV-2 sequences, enabling real-time genomic contact tracing and maintaining an updated reference phylogeny.

Short-range template switching in great ape genomes explored using a pair hidden Markov model

The paper introduces a pair hidden Markov model to detect short-range template switch mutations in great ape genomes and shows their prevalence in evolutionary history.

Stability of SARS-CoV-2 Phylogenies

The paper identifies lab-specific recurrent mutations in SARS-CoV-2 sequences that affect phylogenetic inference and proposes tools to improve sequence quality and phylogeny comparison.

Genomic diversity affects the accuracy of bacterial SNP calling pipelines

This study evaluates SNP calling pipelines' performance on bacterial data, finding that reference genome selection strongly impacts accuracy, with Snippy performing consistently well across diverse genomes.

Comparison of long-read sequencing technologies in the hybrid assembly of complex bacterial genomes

This study compares hybrid assemblies of bacterial genomes using Illumina and long-read sequencing technologies, finding that combining ONT and Illumina reads provides high-quality, low-cost genome reconstruction.

Bayesian Reconstruction of Transmission within Outbreaks using Genomic Variants

This paper introduces BadTrIP, a Bayesian method to infer host-to-host transmission using genomic variants and epidemiological data, showing improved accuracy over existing approaches.

Frequent recombination of pneumococcal capsule highlights future risks of emergence of novel serotypes.

The paper analyzes genetic data to show that pneumococcal capsule recombination generates novel serotypes, highlighting risks for vaccine efficacy.

Evolutionary history of the global emergence of the Escherichia coli epidemic clone ST131

This study traces the evolutionary history of the ST131 E. coli lineage, showing its clonal expansion linked to antibiotic use and plasmid acquisition, with implications for antimicrobial resistance control.