Research and Discovery Solutions

Questions Answered at the Resolution of a Single Cell

Designed for academic, translational, and early-stage industry researchers seeking high-resolution single-cell insight into genomic and transcriptomic variation, our products and services have been used to drive foundational discoveries at the single cell level.

Join the growing number of researchers using BioSkryb products to:

Define somatic mosaicism and track clonal evolution in single cells

Throughout our lifespans, our cells accumulate mutations—benign and pathogenic—and our bodies become a heterogenous mosaic of cells with many genotypes. Researchers use BioSkryb products to describe somatic mosaicism in single cells and nuclei from a variety of tissues, ages, and pathogenic states.

In oncology, researchers are focused on understanding how clonal evolution drives cancer development, recurrence, and therapy resistance. In neurology, researchers are using these acquired mutations as “molecular barcodes” to define how neural tissues, like the neural crest, develop.

Identify on- and off-target edits following gene editing

Gene editing occurs at the level of a single cell. Evaluating on- and off-target edits can be readily achieved with single-cell whole genome sequencing (scWGS). Our researchers demonstrated that scWGS enabled by ResolveDNA® identifies many more off-target edits than predicted by off-target prediction algorithms.

When coupled with ResolveOME™, unified genomic and transcriptomic information allows researchers to understand the functional impact of gene edits on individual cells.

Amplify DNA from low-input samples enabling genomic analysis

From microbiology to forensics to oncology to neurology, researchers have used primary template-directed amplification (PTA) found in ResolveDNA® to amplify low-input DNA samples—enabling analyses not possible before high-fidelity whole genome amplification.

Train and validate AI models

Artificial intelligence (AI) requires accurate training data sets to develop precise algorithms and comprehensive data sets to validate AI models. ResolveOME™ provides unified genomic and transcriptomic data from single cells, allowing researchers to develop machine learning (ML) algorithms, including those that can predict extrachromosomal DNA from single-cell RNA sequencing data.