Rxivist logo

Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 73,081 bioRxiv papers from 318,132 authors.

Batch effects and the effective design of single-cell gene expression studies

By Po-Yuan Tung, John D Blischak, Chiaowen Joyce Hsiao, David A Knowles, Jonathan E Burnett, Jonathan K. Pritchard, Yoav Gilad

Posted 08 Jul 2016
bioRxiv DOI: 10.1101/062919 (published DOI: 10.1038/srep39921)

Single cell RNA sequencing (scRNA-seq) can be used to characterize variation in gene expression levels at high resolution. However, the sources of experimental noise in scRNA-seq are not yet well understood. We investigated the technical variation associated with sample processing using the single cell Fluidigm C1 platform. To do so, we processed three C1 replicates from three human induced pluripotent stem cell (iPSC) lines. We added unique molecular identifiers (UMIs) to all samples, to account for amplification bias. We found that the major source of variation in the gene expression data was driven by genotype, but we also observed substantial variation between the technical replicates. We observed that the conversion of reads to molecules using the UMIs was impacted by both biological and technical variation, indicating that UMI counts are not an unbiased estimator of gene expression levels. Based on our results, we suggest a framework for effective scRNA-seq studies.

Download data

  • Downloaded 2,294 times
  • Download rankings, all-time:
    • Site-wide: 2,128 out of 73,076
    • In genomics: 450 out of 4,853
  • Year to date:
    • Site-wide: 60,908 out of 73,076
  • Since beginning of last month:
    • Site-wide: 60,908 out of 73,076

Altmetric data


Downloads over time

Distribution of downloads per paper, site-wide


PanLingua

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


News