prstools
prstools is software to create Polygenic Risk Scores (PRS) directly
from the commandline.
It makes PRS generation easier, compared to previous tools, by:
- Super fast reading and matching of sumstats (handles odd formats).
- Rapid creation of the model.
- Automatic generation of the PRS Prediction for target plink files.
All the above, for a real GWAS sumstat, within 30 minutes using only 1 command. Installation and running the demo example should not take more than 10 minutes.
We are actively developing prstools and feedback by mail or our feedback form (with 🏆 lottery) is much appreciated!
Install
To install use the following command.
pip install -U --prefer-binary prstools
For it to work, you should have python3.8 or later installed (pip is
included in python3.8+). If the command above does not work directly you
can install using conda (or mamba if you have that), by running
conda install "python>=3.9". For other install issues please check the
install
guide
or send us a mail.
How to use
Immediately after installing prstools, it should be possible to download & run the demo example (~4mb), by pasting the following into the commandline (if not see install guide):
# Makes 'example' dir with data in current path:
prstools downloadutil --pattern example --destdir ./; cd example
# Run the model with example data:
prstools prscs2 --ref ldref_1kg_pop --target target \
--sst sumstats.tsv --n_gwas 2565 --out ./result
This will run PRS-CS2 on the example data, using the new implementation
to demonstrate the capabilities of prstools and makes PRS predictions
for the example dataset. The best and fastest way to get a PRS for your
case is to try the Tutorial below.
There is also the prstools documentation, residing inside of the
command-line interface, which you can see by typing prstools or a
subcommand. Forinstance typing prstools prscs2 will output the
documentation for the prscs2 subcommand:
Usage:
prst prscs2 [-h --cpus <num-of-cpus>] --ref <dir/refcode> --target <bim-prefix>
--sst <file> --out <dir+prefix> [--n_gwas <num> --chrom <chroms>]
[ ... [omitted for readability] ... ]
PRS-CS v2: A polygenic prediction method that infers posterior SNP effect sizes under
continuous shrinkage (CS) priors.
... [omitted for readability] ...
# Examples (get data, run model) --> can be directly copy-pasted (:
prstools downloadutil --pattern example --destdir ./; cd example
prst prscs2 --ref ldref_1kg_pop -t target -s sumstats.tsv --n_gwas 2565 --out result-prscs2
As can be seen, there are examples at the end of the help output to illustrate usage, which should work with a simple copy-paste.
There is now also an online version of all this documentation
(https://prstools.readthedocs.io/).
Tutorial + Video
For more information and a hands on demonstration of what prstools can
do have a look at the Getting Started
Tutorial.
There is also a Video. The
tutorial+video is a tiny bit older than the current prstools version,
which has more functionality. You can load the tutorial in a free cloud
instance by clicking here: 
Contact
For questions and support please send a mail (menno.j.witteveen@gmail.com).
1 maintainer
Metadata
1 maintainer
Release files for prstools 0.0.80
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| prstools-0.0.80.tar.gz | 2.0 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| prstools-0.0.80-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 4.0 MB
Release files / prstools-0.0.80.tar.gz
| Download URL | prstools-0.0.80.tar.gz |
|---|---|
| Size | 2.0 MB |
| Tags | Source |
|
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No |
| Uploaded via |
twine/6.2.0 CPython/3.11.4
|
Release files / prstools-0.0.80-py3-none-any.whl
| Download URL | prstools-0.0.80-py3-none-any.whl |
|---|---|
| Size | 2.0 MB |
| Tags | Python 3 |
|
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.4
|
