Live-cell imaging data for DASC (disassembly asymmetry score classification) analysis of calthrin-mediated endocytosis
This dataset is for
sharing all of the raw images analyzed in the paper, “DASC, a sensitive
classifier for measuring discrete early stages in clathrin-mediated endocytosis”,
In the paper, we proposed a new method that can unbiasedly classify two
populations of clathrin structures during endocytosis, clathrin coated pits and
abortive coats. Based on this new classification, we measured phenotypes of
siRNA knockdown of 11 endocytic accessory protein (EAP), analyzed clathrin-AP2
dual channel images and measured curvature formation during endocytosis.
Images in all four experiments are included in this data set, ‘EAP knockdown’, ‘alphaPIP2-’ as a positive control experiment, ‘CLC_AP2_dual’ as another control experiment, and ‘EpiTIRF’ for curvature measurement. Each experiment has various conditions, see the metadata file for details.
Readers can follow this README to obtain the entire data and then apply DASC, one experiment by one experiment, to reproduce the results in the associated paper. The software of DASC is available on GitHub: https://github.com/DanuserLab/cmeAnalysis. See the instruction on the GitHub page for how to use DASC to analyze the images.
Files in this data are compressed. Each ‘.tif.bz’ file is a compressed tif image sequence of fluorescently labeled cells. The names of these compressed files include descriptive information of ‘experiment’, ‘condition’, ‘date’, ‘cell name’ and ‘channel name’ (optional). These descriptors are separated by ‘#’.
The compressed files can be automatically decompressed by running the Matlab script ('Decompression.m') in a Linux system.