Feature extraction quality control report

ScalableCytometryImageProcessing / SCIP

Scalable Cytometry Image Processing (SCIP) is an open-source tool that implements an image processing pipeline on top of Dask, a distributed computing framework written in Python. SCIP performs projection, illumination correction, image segmentation and masking, and feature extraction.

https://scalable-cytometry-image-processing.readthedocs.io/en/latest/

GNU General Public License v3.0

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Feature extraction quality control report #9

Closed MaximLippeveld closed 3 years ago

MaximLippeveld commented 3 years ago

After feature extraction a quality control report should be saved, which should contain:

[x] A table of extracted features containing a column with the feature name and columns with some basic statistics (mean, variance, median)
[x] Check for zero variance features and add list to report
[x] Plot of dimensionality reduction (see #19), coloured according to meta data (= per sample or per acquisition day)