期刊
HISTOCHEMISTRY AND CELL BIOLOGY
卷 141, 期 6, 页码 605-612出版社
SPRINGER
DOI: 10.1007/s00418-014-1208-z
关键词
Cluster analysis; Super-resolution; Co-localisation; PALM; STORM
资金
- Marie Curie Career Integration Grant (CIG) [334303]
- National Health and Medical Research Council of Australia
- Australian Research Council
We demonstrate a combined univariate and bivariate Getis and Franklin's local point pattern analysis method to investigate the co-clustering of membrane proteins in two-dimensional single-molecule localisation data. This method assesses the degree of clustering of each molecule relative to its own species and relative to a second species. Using simulated data, we show that this approach can quantify the degree of cluster overlap in multichannel point patterns. The method is validated using photo-activated localisation microscopy and direct stochastic optical reconstruction microscopy data of the proteins Lck and CD45 at the T cell immunological synapse. Analysing co-clustering in this manner is generalizable to higher numbers of fluorescent species and to three-dimensional or live cell data sets.
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