Zamin Iqbal

Flex-It is a genotyping framework for S. flexneri that rapidly characterizes genotypes and resistance determinants from sequencing data, enabling standardized surveillance of its population structure and antimicrobial resistance.

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.

Mykrobe k-mer panel genotypes Salmonella Typhi lineages, antimicrobial resistance (AMR) markers and plasmids from Illumina or nanopore reads, matching mapping-based lineage calls for 99.8% of genomes.

This paper develops an automated method to build a comprehensive catalogue of resistance-associated variants for M. tuberculosis, achieving comparable performance to existing catalogues without expert rules.

LexicMap efficiently aligns sequences against millions of prokaryotic genomes, achieving comparable accuracy to existing tools with faster speed and lower memory use.

The paper introduces pling, a tool to cluster plasmid genomes using rearrangement distances, and integrates it with SNP and typing data for genomic epidemiology.

The paper uses long-read sequencing to generate complete genomes of Mycobacterium tuberculosis complex isolates, revealing increased genomic diversity and improved resolution in transmission analysis.

Amira detects AMR genes directly from long reads using gene-space de Bruijn graphs, achieving high recall and accuracy compared to assembly-based methods.

This paper introduces phylogenetic compression to efficiently search large microbial genome collections, achieving significant compression improvements and enabling fast BLAST-like searches on desktop computers.

This study tracks clonal and plasmid transmission in colistin- and carbapenem-resistant K. pneumoniae using short and long read sequencing, revealing complex plasmid networks and highlighting the need for full-length sequencing to understand resistance spread.

This paper introduces pling, a tool that uses rearrangement distances to cluster plasmids more accurately by accounting for structural changes and avoiding over-clustering caused by transposable elements.

The paper compares plasmids from pre-antibiotic era bacteria with modern plasmids to show how resistance genes evolved and spread over time.

CELEBRIMBOR improves core gene identification in metagenome-assembled genomes by adjusting frequency thresholds based on genome completeness.

A uniformly processed set of 2,440,377 bacterial and archaeal genomes with search tools and annotations, plus an AI-mined peptide set yielding ATB20, active in a mouse skin infection model.

The paper describes open data sharing, analysis tools, and lessons learned from the European COVID-19 Data Platform's SARS-CoV-2 data collection and analysis efforts.

This study quantifies antibiotic resistance in tuberculosis using genomic data and MIC measurements to identify genetic determinants of resistance and hypersensitivity across multiple drugs.

This paper develops DrPRG, a tool for predicting drug resistance in Mycobacterium tuberculosis using reference graphs, showing improved sensitivity and specificity compared to existing methods.

ReadItAndKeep removes human contamination from SARS-CoV-2 sequencing data efficiently on low-specification laptops.

Minos integrates variant calls from multiple tools to adjudicate discrepancies and jointly genotype bacterial cohorts, improving accuracy in detecting SNPs and indels.

This paper introduces a pan-genome graph structure and software tool, pandora, to analyze bacterial genomic variation across multiple isolates with higher SNP recovery and lower error rates than existing methods.

The paper introduces a genome graph model and software to genotype multiscale genetic variation across different sequence backgrounds, demonstrating applications in tuberculosis and malaria genomes.

GenTB predicts tuberculosis drug resistance from genomic data using machine learning, achieving higher sensitivity than existing tools with slightly lower specificity.

The paper evaluates short-read variant calling accuracy in Mycobacterium tuberculosis using Illumina and PacBio data, finding high precision with optimized mapping thresholds and identifying 68% of excluded repetitive regions as accurately called.

The paper introduces Corticall, a graph-based method to detect de novo mutations using short-read and long-read data, validated on Plasmodium falciparum crosses.

REINDEER indexes k-mer presence and abundance across large sequencing datasets efficiently, processing 2,585 human RNA-seq experiments in 45 hours with 56 GB RAM.

GenomegaMap estimates genome-wide dN/dS ratios across 10,209 tuberculosis genomes to identify selection pressures shaping the pathogen's evolution.

The paper introduces a DNA search engine for microbial genomic data that enables real-time search and analysis of bacterial and viral sequences.

The paper introduces a new data structure called the Linked de Bruijn Graph (LdBG) that integrates long-range connectivity information into de Bruijn graphs, improving performance in genome assembly and variant calling.

Severe S. aureus infections arise from the nasal microbiome through adaptive evolution, with specific mutations enriched in infecting bacteria compared to colonizing ones.