Our solution takes you from single cell or single-nuclei suspension through library prep and sequencing and delivers immediate results via our analysis software, Trailmaker.
Unparalleled accessibility and scale for single cell research. Up to 5 million cells and 384 samples in a single experiment.
Our user-friendly platform simplifies scRNA-seq data analysis, making it accessible and transparent for researchers.
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Providing researchers single cell sequencing with unprecedented scale and ease
About ParseOur solution takes you from single cell or single-nuclei suspension through library prep and sequencing and delivers immediate results via our analysis software, Trailmaker.
Unparalleled accessibility and scale for single cell research. Up to 5 million cells and 384 samples in a single experiment.
Our user-friendly platform simplifies scRNA-seq data analysis, making it accessible and transparent for researchers.
Unlock the power of single cell RNA-sequencing (scRNA-seq) with Trailmaker. Our user-friendly platform simplifies scRNA-seq data analysis, making it accessible and transparent for researchers. Quickly process, integrate, and explore Evercode Whole Transcriptome data, create publication-ready figures, and share your findings with ease.
Explore Trailmaker (It's free!)Our end-to-end workflow guides you from samples to discoveries, offering flexible entry, stopping, and exit points throughout the entire process, from sample preparation to data analysis.
Trailmaker provides end-to-end analysis of Evercode WT data with flexibility built in to support count matrices from various single-cell technologies. Advanced analysis is enabled through Seurat object download for code-based methods.
Trailmaker’s Pipeline module processes Parse Biosciences Evercode™ WT FASTQ files, generating reports and count matrices for viewing or downloading.
Data is automatically sent to the Insights module for downstream processing and visualization.
You are guided step-by-step through the necessary filtering and integration processes.
Automatically determined default settings deliver ready-to-explore data analysis, with user friendly controls for adjusting filtering thresholds, parameters and methods.
Automated cell type prediction is provided using the ScType algorithm that’s built on an extensive database of cell population markers across tissues and species.
If Leiden or Louvain clusters don’t quite fit your use case, you can generate custom cell sets using the lasso or gene expression features. It’s also easy to combine clusters or to subset specific clusters into a new analysis.
Differential expression analysis calculates the differences in gene expression profiles between clusters or cell populations of interest.
Differential expression results can be filtered, plotted in a Volcano plot, sent for pathway analysis and downloaded.
Pre-loaded plots are available to view, customize and download.
Customization options include:
Calculate trajectories using the Monocle3 algorithm and plot pseudotime in a customizable trajectory plot.
Share individual projects with colleagues or collaborators to work together on data analysis.
Grab a dataset from the Trailmaker datasets repository to start exploring Trailmaker’s data analysis and visualization capabilities today!
This free course is designed specifically for biologists and accessible to all, requiring no coding experience. With a self-paced structure, comprehensive support, and guided learning through Trailmaker, it ensures an efficient and seamless experience.
University of Toronto
Institute of Science and Technology Austria
University of Turku
Learn more about Parse Biosciences' cloud analysis tools.
Parse Biosciences provides a pipeline that can be run on a Linux operating system,
either locally or on a server. The pipeline remains available for
customers to download via our support suite.
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