Rxivist logo

Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 62,736 bioRxiv papers from 278,376 authors.

Evaluating Cell Identity from Transcription Profiles

By Nancy Mah, Katerina Taškova, Khadija El Amrani, Krithika Hariharan, Andreas Kurtz, Miguel A. Andrade-Navarro

Posted 19 Jan 2018
bioRxiv DOI: 10.1101/250431

Induced pluripotent stem cells (iPS) and direct lineage programming offer promising autologous and patient-specific sources of cells for personalized drug-testing and cell-based therapy. Before these engineered cells can be widely used, it is important to evaluate how well the engineered cell types resemble their intended target cell types. We have developed a method to generate CellScore, a cell identity score that can be used to evaluate the success of an engineered cell type in relation to both its initial and desired target cell type, which are used as references. Of 20 cell transitions tested, the most successful transitions were the iPS cells (CellScore > 0.9), while other transitions (e.g. induced hepatocytes or motor neurons) indicated incomplete transitions (CellScore < 0.5). In principle, the method can be applied to any engineered cell undergoing a cell transition, where transcription profiles are available for the reference cell types and the engineered cell type.

Download data

  • Downloaded 445 times
  • Download rankings, all-time:
    • Site-wide: 22,088 out of 62,736
    • In bioinformatics: 3,171 out of 6,251
  • Year to date:
    • Site-wide: 37,945 out of 62,736
  • Since beginning of last month:
    • Site-wide: 34,750 out of 62,736

Altmetric data


Downloads over time

Distribution of downloads per paper, site-wide


Sign up for the Rxivist weekly newsletter! (Click here for more details.)


News