- This package is not currently maintained. A new package that will include all
pygpseqfeatures is being implemented at
- This package has been developed and tested ONLY for Python3.6, which will reach its end of life On December 23rd, 2021.
- Versions 3.4.* of this package only change package dependencies to fix an issue due to incorrect dependency declaration.
A Python3.6 package that provides tools to analyze images of GPSeq samples. Read the Wiki documentation for more details.
Python3.6 and compatible
tkinter package are required to run
On Ubuntu 20.04, you can install them with:
sudo add-apt-repository ppa:deadsnakes/ppa sudo apt install python3.6 sudo apt install python3.6-tk
We recommend installing
Check how to install
if you don't have it yet! Once you have
poetry ready on your system, you can install the
package in its own virtual environment with:
git clone https://github.com/ggirelli/pygpseq.git cd pygpseq poetry install
And then enter the environment with
Alternatively, if you prefer to use
conda , you can setup an environment with:
conda create -n pygpseq python=3.6 conda activate pygpseq conda install pip conda install -c anaconda libtiff
Analyze a GPSeq image dataset
gpseq_anim (GPSeq analysis of images) analyzes a multi-condition GPSeq image dataset. Run
gpseq_anim -h for more details.
Calculate lamin distance of FISH signals
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.
Merge multiple FISH analyses using a metadata table
gpseq_fromfish_merge script to merge multiple FISH analysis output (generated with
gpseq_fromfish). For more details run
Perform automatic 3D nuclei segmentation
tiff_auto3dseg -h for more details on how to produce binary/labeled (compressed) masks of your nuclei staining channels
Identify out of focus (OOF) fields of view
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
ggplot2) can be used to produce an informative plot with the signal location over the Z stack.
Split a tiff in smaller images
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
(Un)compress a tiff
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.
Convert a nd2 file into single-channel tiff images
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.
MIT License Copyright (c) 2017-21 Gabriele Girelli