nf-core/imcyto v1.0.0 - Platinum Panda

[1.0.0] - 2020-05-29

Initial release of nf-core/imcyto, created with the nf-core template.

Pipeline summary

1. Split image acquisition output files (mcd, ome.tiff or txt) by ROI and convert to individual tiff files for channels with names matching those defined in user-provided metadata.csv file. Full and ilastik stacks will be generated separately for all channels being analysed in single cell expression analysis, and for channels being used to generate the cell mask, respectively (imctools).

2. Apply pre-processing filters to full stack tiff files (CellProfiler).

3. Use selected tiff files in ilastik stack to generate a composite RGB image representative of the plasma membranes and nuclei of all cells (CellProfiler).

4. Use composite cell map to apply pixel classification for membranes, nuclei or background, and save probabilities map as tiff (Ilastik). If CellProfiler modules alone are deemed sufficient to achieve a reliable segmentation mask this step can be bypassed using the --skip_ilastik parameter in which case the composite tiff generated in step 3 will be used in subsequent steps instead.

5. Use probability/composite tiff and pre-processed full stack tiff for segmentation to generate a single cell mask as tiff, and subsequently overlay cell mask onto full stack tiff to generate single cell expression data in csv file (CellProfiler).