Sergey Knyazev

The paper describes a biobank initiative that links genomic data with electronic health records to enable genome-wide and phenome-wide association studies across diverse populations.

This paper meta-analyzes single-cell method benchmarks to identify challenges in extensibility, interoperability, and reproducibility.

The paper explores the relationship between genomic ancestry and health outcomes using a biobank linked to electronic health records, finding disease stratification across ancestry clusters.

This paper clusters SARS-CoV-2 sequences to identify variants and subtypes, showing improved performance over existing methods and detecting rare variants in large datasets.

MicrobeTrace integrates and analyzes multi-source public health data to support rapid outbreak response, demonstrating its utility with HIV and SARS-CoV-2 datasets.

This paper introduces CliqueSNV, a method to accurately identify minority viral haplotypes from NGS data by reducing sequencing noise, achieving detection at frequencies as low as 0.1%.

This paper introduces a method using k-mer distribution in RNA-seq reads to estimate genetic relatedness between viral samples and infer transmission clusters without requiring full RNA-seq assembly.

This study benchmarks error-correction methods for next-generation sequencing data, finding significant variation in performance across datasets with no single method being optimal overall.

This paper evaluates scaffolding tools by accounting for repeats in genomic sequences, proposing a repeat-aware evaluation framework and applying it to assess state-of-the-art tools on GAGE datasets.