Highly multiplexed immunofluorescence images and single-cell data of immune markers in tonsil and lung cancer
| العنوان: | Highly multiplexed immunofluorescence images and single-cell data of immune markers in tonsil and lung cancer |
|---|---|
| المؤلفون: | Jia-Ren Lin, Rumana Rashid, Jeremy L. Muhlich, Clarence Yapp, Sandro Santagata, Artem Sokolov, Zoltan Maliga, Yu-An Chen, Peter K. Sorger, Giorgio Gaglia, Denis Schapiro, Ziming Du |
| المصدر: | Scientific Data, Vol 6, Iss 1, Pp 1-10 (2019) Scientific Data |
| بيانات النشر: | Cold Spring Harbor Laboratory, 2019. |
| سنة النشر: | 2019 |
| مصطلحات موضوعية: | Statistics and Probability, Data Descriptor, Lung Neoplasms, Tissue Fixation, Computer science, Palatine Tonsil, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Fluorescent Antibody Technique, Immune markers, Library and Information Sciences, Immunofluorescence, Education, 03 medical and health sciences, 0302 clinical medicine, Image processing, Formaldehyde, Biomarkers, Tumor, medicine, Humans, lcsh:Science, Lung cancer, 030304 developmental biology, 0303 health sciences, Artifact (error), Paraffin Embedding, medicine.diagnostic_test, Extramural, business.industry, Diagnostic markers, Pattern recognition, medicine.disease, Fluorescence, Computer Science Applications, 3. Good health, ComputingMethodologies_PATTERNRECOGNITION, medicine.anatomical_structure, 030220 oncology & carcinogenesis, Tonsil, Cancer imaging, lcsh:Q, Artificial intelligence, Single-Cell Analysis, Statistics, Probability and Uncertainty, business, Algorithms, Software, Information Systems |
| الوصف: | 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. Measurement(s)immunofluorescence • biomarker • cellular featureTechnology Type(s)immunofluorescence microscopy assay • computational modeling techniqueFactor Type(s)Lung carcinoma • Reactive tonsilSample Characteristic - OrganismHomo sapiens Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11184539 |
| الوصول الحر: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::356c5b55e37f4959bbbeb21cd06d20a0Test https://doi.org/10.1101/704114Test |
| حقوق: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....356c5b55e37f4959bbbeb21cd06d20a0 |
| قاعدة البيانات: | OpenAIRE |
| الوصف غير متاح. |