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Companion repository for the paper 'Compensation of signal spillover in suspension and imaging mass cytometry'
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cyTOF compensation

This repository contains scripts used to reproduce a majority of figures from the paper "Compensation of signal spillover in suspension and imaging mass cytometry" by Stéphane Chevrier*, Helena L. Crowell*, Vito R.T. Zanotelli*, Stefanie Engler, Mark D. Robinson, and Bernd Bodenmiller which is published in 'Cell Systems' as "Compensation of Signal Spillover in Suspension and Imaging Mass Cytometry" (http://www.cell.com/cell-systems/abstract/S2405-4712(18)30063-2)

The bioRxiv version was made available under the name "Channel crosstalk correction in suspension and imaging mass cytometry": https://www.biorxiv.org/content/early/2017/09/07/185744

The raw data is available from Mendeley data under the DOI code 10.17632/v58yj49pfr The CATALYST package developed specifically to allow a user friendly usage of the developped spillover estimation and compensation approach can be found for download at: http://bioconductor.org/packages/CATALYST A link to the light version of the web app, installation instructions, example datasets, and vignettes for CATALYST are available from the project page: https://catalyst-project.github.io/.

The repository is organized in the following scripts:

  1. retrieve_data.R:
    Retrieves the data from the Mendeley repository. If you want to run the scripts below this needs to be run first.

Flow mass cytometry compensation

  1. dilution_series.Rmd:
    code
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    html
    Assesses the linearity of spillover based on a dilution series of antibody staining This will reproduce, among other plots, the following figures from the paper:
  • Figure 1, C
  1. even_odd.Rmd:
    code
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    Assessment of compensation accuracy for single stained beads vs. multiplexed cells. Reproduces:
  • Figure 2, C
  1. bc_titration.Rmd:
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    Support for our hypothesis that the difference observed in spillover between single-stained beads and multiplexed-stained cells is due to saturation effects. Reproduces:
  • Figure 2, D+E
  1. correlation_analysis.Rmd:
    code
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    Explore how spillover and compensation affect correlations and phenograph clusters in a cyTOF dataset. This will reproduce, among other plots, the following figures from the paper:
  • Figure 3, A-E
  • Figure S4, A-C
  1. spillmat_estimation_stability.Rmd:
    code
    markdown
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    Comparison and stability analysis of spillover matrices obtained from 11 single stained bead replicates, 2 IMC measurements, and Fluidigm. Reproduces:
  • Figure S3, B-E
  • Figure S5, B-E
  1. method_comparison.Rmd:
    code
    markdown
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    Compares different methods for spillover estimation. Reproduces:
  • Figure S2, C-F
  1. plotting-wrappers.R:
    code
    Contains helper functions to plot the results of the above scripts.

Imaging mass cytometry compensation

  1. imc_generatespillmat_long.Rmd:
    code
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    A detailed step by step script to calculate a spillover matrix from a single stain experiment. Reproduces:
  • Figure S5, A
  • Figure 4, A
  1. imc_generatespillmat_short.Rmd:
    code
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    A short version of a script to generate a spillover matrix from an IMC single stain experiment in one step using a convenience function

  2. imc_preprocessing.ipynb:
    code
    A script to convert & process IMC images for segmentation. Adapted from: https://github.com/BodenmillerGroup/ImcSegmentationPipeline The CellProfiller & ilastik pipelines that were used for the IMC image analysis can be found in the data/IMC_image/pipelines

The segmentation output produced by the IMC image analysis is then analysed in script 7). The compensated images saved were used in ImageJ to reproduce Figure 4, B

  1. imc_adaptsm.Rmd:
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    Adapts the spillover matrix and saves it as a TIFF for usage in the CellProfiller pipeline.

  2. imc_cpoutput_analysis.Rmd:
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    Script that was used to compensate the CellProfiller output and display the segmented data on the masks. Reproduces:

  • Figure 3, D and produces the mask images visualized in Fig 4 C using ImageJ
  1. spillover_imc_helpers.R:
    code
    Contains various helper functions used in the scripts above.

Bonus scripts:

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