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Identification of spatial expression trends in single-cell gene expression data

Nature Methods 15, 339–342 (2018) | Download Citation

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Abstract

As methods for measuring spatial gene expression at single-cell resolution become available, there is a need for computational analysis strategies. We present trendsceek, a method based on marked point processes that identifies genes with statistically significant spatial expression trends. trendsceek finds these genes in spatial transcriptomic and sequential fluorescence in situ hybridization data, and also reveals significant gene expression gradients and hot spots in low-dimensional projections of dissociated single-cell RNA-seq data.

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Acknowledgements

This work was supported by the Swedish Research Council (grant 2017-01062 to R.S.), the European Research Council (grant 648842 to R.S.) and the Bert L. and N. Kuggie Vallee Foundation (R.S.).

Author information

Affiliations

  1. Department of Cell and Molecular Biology, Karolinska Institutet, Stockholm, Sweden.

    • Daniel Edsgärd
    • , Per Johnsson
    •  & Rickard Sandberg

  2. Ludwig Institute for Cancer Research, Stockholm, Sweden.

    • Daniel Edsgärd
    • , Per Johnsson
    •  & Rickard Sandberg

Authors

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Contributions

D.E. conceived the idea, developed the method, performed the analyses and wrote the manuscript. P.J. performed seqFISH and clustering analyses. R.S. supervised the project and wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Rickard Sandberg.

Integrated supplementary information

Supplementary figures

  1. 1.

    Power analysis of trendsceek.

  2. 2.

    trendsceek sensitivity depends on relative differences and not magnitude scale.

  3. 3.

    Comparing trendsceek results with the identification of variable genes.

  4. 4.

    Comparison of trendsceek mark-segregation summary statistics.

  5. 5.

    trendsceek statistics for significant genes from mouse olfactory bulb spatial transcriptomics data.

  6. 6.

    Spatial expression patterns identified in spatial transcriptomics mouse olfactory bulb data.

  7. 7.

    trendsceek statistics for significant genes from spatial transcriptomics breast cancer data.

  8. 8.

    Spatial expression patterns identified in spatial transcriptomics breast cancer data.

  9. 9.

    trendsceek statistics for significant genes from mouse gastrulation single-cell RNA-seq data.

  10. 10.

    Spatial expression patterns identified in mouse gastrulation single-cell RNA-seq data.

  11. 11.

    trendsceek statistics for selected significant genes from mouse hippocampus seqFISH data.

  12. 12.

    Spatial gene expression patterns found in regions of mouse hippocampus from seqFISH data.

  13. 13.

    Comparison of genes identified by trendsceek with genes from a differential expression analysis using cell cluster information.

  14. 14.

    Comparison of gene rankings between trendsceek and gene variability.

  15. 15.

    Runtime of trendsceek on different data sets.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–15

  2. 2.

    Life Sciences Reporting Summary

Excel files

  1. 1.

    Supplementary Table 1

    Number of significant genes identified with the different spatial trend metrics

  2. 2.

    Supplementary Table 2

    List of genes with significant spatial expression patterns in spatial transcriptomics data from mouse olfactory bulb (replicate 3)

  3. 3.

    Supplementary Table 3

    List of cells with significant spatial expression patterns in spatial transcriptomics data from mouse olfactory bulb (replicate 3)

  4. 4.

    Supplementary Table 4

    List of genes with significant spatial expression patterns in spatial transcriptomics data from mouse olfactory bulb (replicate 12)

  5. 5.

    Supplementary Table 5

    List of cells with significant spatial expression patterns in spatial transcriptomics data from mouse olfactory bulb (replicate 12)

  6. 6.

    Supplementary Table 6

    List of genes with significant spatial expression patterns in spatial transcriptomics data from breast cancer (layer 2)

  7. 7.

    Supplementary Table 7

    List of cells with significant spatial expression patterns in spatial transcriptomics data from breast cancer (layer 2)

  8. 8.

    Supplementary Table 8

    List of genes with significant spatial expression patterns in dissociated single-cell RNA-seq data from mouse embryo

  9. 9.

    Supplementary Table 9

    List of cells with significant spatial expression patterns in dissociated single-cell RNA-seq data from mouse embryo

  10. 10.

    Supplementary Table 10

    List of genes with significant spatial expression patterns in seqFISH data from mouse hippocampus

  11. 11.

    Supplementary Table 11

    List of cells with significant spatial expression patterns in seqFISH data from mouse hippocampus

Zip files

  1. 1.

    Supplementary Software

    trendsceek package

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DOI

https://doi.org/10.1038/nmeth.4634

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