Highly multiplexed immunofluorescence images and single-cell data of immune markers in tonsil and lung cancer

Sci Data. 2019 Dec 17;6(1):323. doi: 10.1038/s41597-019-0332-y.


In this data descriptor, we document a dataset of multiplexed immunofluorescence images and derived single-cell measurements of immune lineage and other markers in formaldehyde-fixed and paraffin-embedded (FFPE) human tonsil and lung cancer tissue. We used tissue cyclic immunofluorescence (t-CyCIF) to generate fluorescence images which we artifact corrected using the BaSiC tool, stitched and registered using the ASHLAR algorithm, and segmented using ilastik software and MATLAB. We extracted single-cell features from these images using HistoCAT software. The resulting dataset can be visualized using image browsers and analyzed using high-dimensional, single-cell methods. This dataset is a valuable resource for biological discovery of the immune system in normal and diseased states as well as for the development of multiplexed image analysis and viewing tools.

Publication types

  • Dataset
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Biomarkers, Tumor / immunology*
  • Fluorescent Antibody Technique*
  • Formaldehyde
  • Humans
  • Lung Neoplasms / immunology*
  • Palatine Tonsil / immunology*
  • Paraffin Embedding
  • Single-Cell Analysis*
  • Software
  • Tissue Fixation


  • Biomarkers, Tumor
  • Formaldehyde