GOOSE is a python package developed to make the generation of IDRs or IDR variants easy. Basically, we want to make it easy for you to design IDRs or IDR variants for your research.
There are four main functionalities currently in GOOSE.
1. Generate synthetic IDRs where you can specify the length and:
• properties including average hydropathy, fraction of charged residues (FCR), net charge per residue (NCPR), and kappa (which is a property that defines opposite charge distribution in a sequence),
• fractions of amino acids (you can specify multiple fractions simultaneously), or
• ensemble dimensions, either end-to-end distance (Re) or radius of gyration (Rg)
2. Generate IDR variants. There are over 16 different kinds of sequence variants in GOOSE, and they are intended to change your IDR of interest in ways that let you test different hypotheses.
3. Make sequence libraries spanning sequence properties or fractions of amino acids.
4. Analyze sequences.
You can use GOOSE from Python or from a Google Colab notebook. The Colab notebook can be found at https://colab.research.google.com/drive/1U9B-TfoNEZbbjhPUG5lrMPS0JL0nDB3o?usp=sharing
Right now you can only install GOOSE through Github. It will be on PyPi to allow for pip installation soon!
GOOSE has a few requirements prior to installation. Just follow the steps below to use GOOSE!
First install cython and numpy.
$ pip install cython
$ pip install numpy
Now you can install GOOSE.
To install directly from the git repository simply run:
$ pip install git+https://github.com/idptools/goose.git
Or to clone the GitHub repository and install locally run -
$ git clone https://github.com/idptools/goose.git
$ cd goose
$ pip install .
Important note
GOOSE requires the package sparrow. Sparrow should be downloaded automatically just by pip installing GOOSE, but if you have issues, try installing it by running:
$ pip install git+https://github.com/holehouse-lab/sparrow.git
This will install SPARROW. Important note: if your attempted install of SPARROW fails, it may be because you do not have numpy or cython installed. I made them both required for installation of GOOSE, so if you install GOOSE first, you should be ok. See step 1. of Installation for instructions on installing cython and numpy.
Documentation for GOOSE can be found at https://goose.readthedocs.io/en/latest/index.html.
You can not currently cite GOOSE as we have yet to publish it (hopefully soon!). We would appreciate if you would mention GOOSE in your methods section with a link to the Github page so readers of your paper can understand how you generated the sequences you used.
The section below logs changes to GOOSE.
Version unchaged - continued work on sequence_optimization functionality and a small bug fix (November 2024)
- Continued work on adding the ability to optimized sequences based on any user-defined parameter including ones not hardcoded into GOOSE.
- In line documentation was completed and additional testing of the code was completed. Multiple bugs were fixed.
- A bug where the error allowed when using the create.seq_rg() function was equal to the error for create.seq_re, which was incorrect.
- Added functionality for sequence optimization by total epsilon and epsilon attractive / repulsive vectors
Added in tests to many thousands (maybe millions) of sequences that span sequence parameter space and sequence fraction space. Using these tests, I found some very edge case bugs in GOOSE. These bugs have been fixed. Additionally, some of the backend code has been updated to be more efficient, which will increase the speed at which GOOSE can generate sequences. Also added more information on GOOSE's ability to make sequences at the edge of kappa values. Finally, synthetic sequence creation when kappa is specified has been made to be a bit faster.
Wrote up tests for nearly all possible combinations of creating sequences by specifying different numbers of sequence properties. Found some bugs along the way and fixed them (as far as I can tell). Generally made sequence generation more robust across parameter space. Fixed some issues with exceptions. Updated minimum kappa parameter to a value of 0.03 because GOOSE often has a hard time getting to 0.0. Also increased max hydropathy value that GOOSE can generate to 6.6 on the adjusted Kyte-Doolittle scale.
Made sequence generation by specifying radius of gyration or end-to-end distance user-facing. It was hiding in the backend code for some time now but I finally had time to make the user-facing functionality and write up the docs :). The user facing functions are called seq_re() and seq_rg(). Added sequence variants that alter Re and Rg called re_var() and rg_var(), respectively. Added helicity predictions to analyze functionality.
Fixed bug where sequences with high FCR specified could not have a high enough hydropathy value using the create.sequence() function. Added ability to exclude residues from sequence generated using the create.sequence() function (cannot exclude charged residues when FCR / NCPR are specified). Improved range of kappa values that could be specified. Improved performance of some backend functionality. Fixed some additional edge case bugs. Changed name of shuffle_var() to region_shuffle_var() due to previous addition of other types of shuffle variants. Added more tests.
Initial release. Begin tracking changes.
Funding This project was supported by grants from agencies including the National Science Foundation (NSF), the National Institute of Health (NIH).
Development Development of GOOSE was led primarily by Ryan Emenecker. Numerous ideas were contributed from others along the way including from Shahar Sukenik, Alex Holehouse, and many more.
Cookiecutter Project based on the Computational Molecular Science Python Cookiecutter version 1.6.
Copyright (c) 2023, Ryan Emenecker - Holehouse Lab