Normalization of single-cell RNA-seq counts by log(x+1)* or log(1+x)*

  1. A. Sina Booeshaghi
  2. Lior Pachter

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Abstract

Single-cell RNA-seq technologies have been successfully employed over the past decade to generate many high resolution cell atlases. These have proved invaluable in recent efforts aimed at understanding the cell type specificity of host genes involved in SARS-CoV-2 infections. While single-cell atlases are based on well-sampled highly-expressed genes, many of the genes of interest for understanding SARS-CoV-2 can be expressed at very low levels. Common assumptions underlying standard single-cell analyses don’t hold when examining low-expressed genes, with the result that standard workflows can produce misleading results.

Key Points

  • Lowly expressed genes in single-cell RNA-seq can be easliy misanalyzed.

  • log(1+x) count normalization introduces errors for lowly expressed genes

  • The average log(1+x) expression differs considerably from log(x) when x is small

  • An alternative approach is to use the fraction of cells with non-zero expression

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    1. ScreenIT

      SciScore for 10.1101/2020.05.19.100214: (What is this?)

      Please note, not all rigor criteria are appropriate for all manuscripts.

      Table 1: Rigor

      Institutional Review Board Statementnot detected.
      Randomizationnot detected.
      Blindingnot detected.
      Power Analysisnot detected.
      Sex as a biological variablenot detected.

      Table 2: Resources

      No key resources detected.

      Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

      Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

      Results from TrialIdentifier: No clinical trial numbers were referenced.

      Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

      Results from JetFighter: We did not find any issues relating to colormaps.

      Results from rtransparent:
      • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
      • No funding statement was detected.
      • No protocol registration statement was detected.

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    2. Version published to 10.1101/2020.05.19.100214 on bioRxiv