David Posada

This study evaluates six methods for calling single-nucleotide variants from scRNA-seq data and finds that some methods provide phylogenetically informative genotype calls, with implications for understanding cancer progression.

This study evaluates virome protocols to optimize recovery of human fecal viral genomes while minimizing contamination.

The paper uses single-cell whole-genome sequencing and Bayesian phylodynamic modeling to show colorectal tumors often originate decades before diagnosis and expand rapidly in the last two years.

DelSIEVE infers cell phylogeny and variants from scDNA-seq data, improving detection of deletions and evolutionary events compared to existing methods.

The paper examines genomic diversity within the MDA-MB-231 breast cancer cell line across sublines, identifying intraline heterogeneity driven by single nucleotide variants and copy number alterations.

SIEVE jointly infers somatic variants and cell phylogeny from scDNA-seq data, showing improved accuracy in both tasks compared to existing methods.

This study compares genomic profiling of circulating tumor cells (CTCs) using three methods in metastatic colorectal cancer, finding differences in mutational burden and diversity estimates.

This study sequences single-cell mitochondrial genomes from colorectal cancer patients to investigate mtDNA heteroplasmy in normal and tumor cells.

CellPhy infers single-cell phylogenies from scDNA-seq data using a maximum likelihood framework, showing robustness to errors and superior accuracy and speed compared to existing methods.

The paper sequenced mitochondrial genomes of marine clams with transmissible cancers, revealing a single neoplastic lineage that spreads between species in Southern Europe.

This study analyzes over 7,000 SARS-CoV-2 datasets to reveal genomic diversity, showing iSNVs and small indels drive variation, and highlights implications for qRT-PCR and transmission tracking.

The paper identifies a pan-genome in the Mediterranean mussel with 25% of genes subject to presence/absence variation, suggesting an adaptive strategy for resilience and invasiveness.

ModelTest-NG is a faster and more feature-rich tool for selecting DNA and protein evolutionary models, with improved accuracy and new functionalities.

This study evaluates somatic variant calling methods on multiregional tumor data, finding that multisample approaches do not always outperform single-sample methods, with Mutect2 in multisample mode performing best under challenging conditions.

This study compares six single-cell whole-genome amplification methods using human cells, finding that REPLIg performs best in DNA yield and uniformity while Ampli1 shows fewer technical artifacts.

This study evaluates how sequencing depth affects single-cell cancer genomics, finding that depths >5x do not significantly improve variant detection or phylogenetic reconstruction for large sample sizes.

NGSphy simulates next-generation sequencing data for phylogenomic analysis, assessing how technical and methodological choices affect phylogenetic tree inference.

The paper shows that using bulk tumor data can lead to incorrect evolutionary inferences in cancer studies.

This study evaluates partitioning strategies in phylogenomic datasets, finding that statistical methods and a priori model assignments improve accuracy, while unpartitioned data reduce tree quality.