Discover scalable, instrument-free single cell sequencing technology from Parse Bioscience

Technology Overview


Explore our collection of resources to learn more about technology and its applications from leading researchers

Resources Overview


Providing researchers single cell sequencing with unprecedented scale and ease

About Parse


Discover scalable, instrument-free single cell sequencing technology from Parse Bioscience

Technology Overview

Publications and Posters

Parse has an ecosystem of products to help take your single cell research further. Delve deeper into the details here.


  • WT Mini
  • Human Liver
  • +1

Characterization of Pro-Fibrotic Signaling Pathways using Human Hepatic Organoids

Yuan Guan, Zhuoqing Fang, Angelina Hu, Sarah Roberts, Meiyue Wang, Wenlong Ren, Patrik K. Johansson, Sarah C. Heilshorn, Annika Enejder, Gary Peltz

To address the limitations of traditional in vitro systems and animal models for studying liver fibrosis, this study introduces a novel live cell imaging system in conjunction with microHOs to understand liver fibrosis signal pathways and evaluate anti-fibrotic treatments. ScRNA-Seq was used to explore PDGFβ and TGFβ1’s pro-fibrotic effects on microHOs, revealing significant differences in cell composition and gene expression between treated and control groups.

  • WT
  • Nuclei

Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens

Longda Jiang, Carol Dalgarno, Efthymia Papalexi, sabella Mascio, Hans-Hermann Wessels, Huiyoung Yun, Nika Iremadze, Gila Lithwick-Yanai, Doron Lipson, Rahul Satija

The identification of casual relationships between genes across different biological contexts is limited due to the challenges of scale and cost. Here, the authors demonstrate the integration of multiple new technologies; CRISPR screens and Evercode scRNA-seq (perturb-seq), alongside high-throughput sequencing and the development of new analytical methods to identify differentially expressed genes and discrete regulatory networks at scale. Their example is a framework for a systematic approach to developing an ‘atlas’ of perturbation relationships.

  • WT Mega
  • Mouse Brain

Single nuclei transcriptomics in diabetic mice reveals altered brain hippocampal endothelial cell function, permeability, and behavior

Saivageethi Nuthikattu, Dragan Milenkovic, Jennifer E. Norman, Amparo C. Villablanca

To characterize the molecular mechanisms of Type 2 diabetes-associated dementia, the authors used the Evercode WT Mega in diabetic (db/db) mice’s hippocampal endothelial nuclei. They found changes to transcription factors for endothelial cell function and cell signaling associated with neuroinflammation and cognitive impairment and the downregulation of the pathways tied to cell maintenance and proliferation. The significant correlation between these findings in db/db mice and similar patterns in persons with Alzheimer’s disease and vascular dementia further supports the hypothesis of altered signaling pathways in hippocampal endothelial cells is involved in Type 2 diabetes neurodegeneration.

  • WT
  • PBMCs

Comparative analysis of single-cell RNA sequencing methods with and without sample multiplexing

Yi Xie, Huimei Chen, Vasuki Ranjani Chellamuthu, Ahmad bin Mohamed Lajam, Salvatore Albani, Andrea Hsiu Ling Low, Enrico Petretto, Jacques Behmoaras

Parse and 10X were compared using scRNA-seq on PBMC from 2 healthy donors. Parse demonstrated better data quality with lower multiplets rates but had lower cell recovery. Parse detected 1.2-fold more genes, had better clustering performance, and greater power in distinguishing cell types with specific gene signatures. Parse also excelled in detecting longer transcripts and rare cell types.