/proMAD

Primary LanguagePythonMIT LicenseMIT

proMAD

Semiquantitative densitometric measurement of protein microarrays

PyPi Status License

Github issues Coverage Build

DOI Documentation

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.