Lisa Anderson

This paper introduces a standards framework for integrating single-cell and spatial omics data into brain cell atlases, enabling interoperable and reusable knowledge-ready resources.

This study benchmarks six duplex sequencing technologies to evaluate their performance in detecting somatic mutations across different genomic contexts and tissue types.

The paper uses single-cell DNA sequencing to analyze somatic mosaicism in postmortem lung and colon tissues, revealing mutation heterogeneity, chromosomal abnormalities, and cellular ancestry.

The paper benchmarks somatic variant and indel detection at low allele fractions using short- and long-read data, finding sensitivity and precision around 80% at 300x coverage.