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


ABSTRACT: 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.

SUBMITTER: Rashid R 

PROVIDER: S-EPMC6917801 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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

Rashid Rumana R   Gaglia Giorgio G   Chen Yu-An YA   Lin Jia-Ren JR   Du Ziming Z   Maliga Zoltan Z   Schapiro Denis D   Yapp Clarence C   Muhlich Jeremy J   Sokolov Artem A   Sorger Peter P   Santagata Sandro S  

Scientific data 20191217 1


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 sing  ...[more]

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