proMAD 0.3.2

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Description:

proMAD 0.3.2

proMAD
Semiquantitative densitometric measurement of protein microarrays








Setup
pip install proMAD

You can also install the latest version directly from GitHub.
pip install -U git+https://github.com/theia-dev/proMAD.git#egg=proMAD

Usage
ArrayAnalyse
from proMAD import ArrayAnalyse
aa = ArrayAnalyse('ARY022B') # set array type
aa.load_collection('tests/cases/prepared', rotation=90) # set input folder

aa.evaluate("A6") # get result dictionary
aa.get_spot("A6") # get underlying image data
aa.evaluate() # get result dictionary for all spots

aa.report('report.xlsx') # export the results

Cutter

interactive

from proMAD import Cutter
c = Cutter()

c.load_collection('tests/cases/raw') # set input folder
c.set_shape() # ask for the shape
c.guess_positions() # use a simple guess as a starting point
c.preview() # display guess (uses the last loaded image as default)

c.set_positions() # ask for refined cut positions
c.set_names() # ask for names
c.preview() # check in the preview
c.save_images('test/cases/formatted_image_folder') # save to folder (will be created if it does not exist)


direct

from proMAD import Cutter

c = Cutter()

c.load_collection('tests/cases/raw') # set input folder
c.shape = (2, 3)
c.cut_positions = [[20, 225, 445], [40, 130, 217, 315]]
c.names = [['OL', 'ML', 'UL'], [None, 'MR', 'UR']]
c.preview()
c.save_images('test/cases/formatted_image_folder') # save to folder (will be created if it does not exist)

Citation
If you use proMAD in your work please cite the following article.

Jaeschke, A., Eckert, H. & Bray, L.J.
proMAD: semiquantitative densitometric measurement of protein microarrays.
BMC Bioinformatics 21, 72 (2020).
doi: 10.1186/s12859-020-3402-4


The full source code can be accessed on GitHub with the corresponding documentation hosted at Read the docs.

License:

For personal and professional use. You cannot resell or redistribute these repositories in their original state.

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