A Python3 package that provides tools to analyze images of GPSeq samples.
- Read the GitHub pages documentation for more details.
- Read the Wiki documentation for more details.
Wiki docs will be merged with GitHub pages ones soon.
To install, run the following:
git clone http://github.com/ggirelli/pygpseq
cd pygpseq
sudo -H pip3 install .
To uninstall run the following from within the repository folder:
sudo -H pip3 uninstall pygpseq
To update, first uninstall, and then run the following from within the repository folder.
git pull
sudo -H pip3 install .
The gpseq_anim (GPSeq analysis of images) analyzes a multi-condition GPSeq image dataset. Run gpseq_anim -h for more details.
The gpseq_fromfish script characterizes FISH signals identified with DOTTER (or similar tools) by calculating: absolute/normalized distance from lamina and central region, nuclear compartment, allele status,... Run gpseq_fromfish -h for more details.
Use the gpseq_fromfish_merge script to merge multiple FISH analysis output (generated with gpseq_fromfish). For more details run gpseq_fromfish_merge -h.
Run tiff_auto3dseg -h for more details on how to produce binary/labeled (compressed) masks of your nuclei staining channels
Run tiff_findoof -h for more details on how to quickly identify out of focus fields of view. Also, the tiff_plotoof script (in R, requires argparser and ggplot2) can be used to produce an informative plot with the signal location over the Z stack.
To split a large tiff to smaller square images of size N x N pixels, run tiff_split input_image output_folder N. Use the --enlarge option to avoid pixel loss. If the input image is a 3D stack, then the output images will be of N x N x N voxels, use the --2d to apply the split only to the first slice of the stack. For more details, run tiff_split -h.
To uncompress a set of tiff, use the tiffcu -u command. To compress them use the tiffcu -c command instead. Use tiffcu -h for more details.
Use the nd2_to_tiff tool to convert images bundled into a nd2 file into separate single-channel tiff images. Use nd2_to_tiff -h for the documentation.
We welcome any contributions to pygpseq. Please, refer to the contribution guidelines if this is your first time contributing! Also, check out our code of conduct.
MIT License
Copyright (c) 2017 Gabriele Girelli