Single-cell sequencing reveals what each cell is doing
QIAGEN’s acquisition of Parse Biosciences integrates Evercode’s instrument-free, massively scalable single-cell technology into the Sample to Insight portfolio. The platform enables researchers to analyze cellular heterogeneity within complex tissues, tracing immune cell responses to infection, profiling tumor diversity in oncology and examining transcriptional changes in neurodegenerative disorders such as Parkinson’s or Alzheimer’s disease.
Why single cells matter
The founders of Parse Biosciences, Alex Rosenberg and Charlie Roco, explain how single-cell sequencing helps researchers understand what individual cells are doing and why they are excited to bring this technology to QIAGEN.
Why biology requires single-cell resolution
In most biological studies, millions of cells are analyzed together as a pooled sample. While powerful, these bulk approaches average gene expression signals across all cells, masking important differences between cell types and functional states. Rare tumor subclones, transient immune cell populations or early developmental intermediates may represent less than 1% of a sample, yet their signals disappear when averaged with surrounding cells. Single-cell analysis addresses this limitation by resolving gene expression patterns at the level of individual cells.
Parse’s split-pool combinatorial indexing enables millions to billions of uniquely barcoded transcriptomes without specialized microfluidic instruments, allowing researchers to design statistically robust studies across oncology, immunology and developmental biology.
Workflow: How single-cell sequencing works
July 2026