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Convenient and powerfull Polygenic Risk Score creation.

Project description

prstools

prstools is software to create Polygenic Risk Scores (PRS) directly from the commandline
(and optionally from inside python).

It contains various tools to make PRS generation easier. 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 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 installed using conda (or mamba if you have that), by running conda install "python>=3.9" For other install issues please check the (install guide is still pretty basic) install guide or send us a mail.

How to use

Next to this very brief discription of what prstools can do, there is also more complete Getting Started Tutorial. 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 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 --pred ./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.


More generally you can use prstools by typing into the command-line interface:

prstools
Usage:
 prstools <command> ...

Convenient and powerfull Polygenic Risk Score creation. 
'prst' is a commandline shorthand for 'prstools'

Models & Utility Commands:
 <command>
  downloadutil  Download and unpack LD reference panels and other data.
  combine       A tool to combine genetics-related text files.
  prscs2        PRS-CS v2: A polygenic prediction method that infers posterior SNP effect sizes
                under continuous shrinkage (CS) priors.


By combining prstools with another <command> a specific model or other functionality can be used.
Forinstance typing prstools prscs2 will output a help for the prscs2 subcommand:

Usage:
 prstools prscs2 [-h  --cpus <number-of-cpus>] --ref <dir/refcode> --target <bim-prefix>
                       --sst <file> --out <dir+prefix> [--n_gwas <num>  --chrom <chroms>]
                       [--colmap <alternative_colnames>  --pred  --n_iter <n_iter>]
                       [--n_burnin <n_burnin>  --n_slice <n_slice>  --seed <seed>  --a <a>]
                       [--b <b>  --phi <phi>  --clip <clip>  --sampler <sampler>]

PRS-CS v2: A polygenic prediction method that infers posterior SNP effect sizes under continuous shrinkage (CS) priors.

General Options:
 -h, --help                               Show this help message and exit.
 -c, --cpus <number-of-cpus>              The number of cpus to use. Generally most efficient if
                                          chosen to be between 1 and 5. Functionality can be

... [omitted for readability] ...


 --clip <clip>                            Clip parameter. The default works best in pretty much
                                          all cases. (default: 1.0)
 --sampler <sampler>                      Sampler algorithm. Rue sampling is the original sampler,
                                          which gives good results. (default: Rue)

Examples --> can be directly copy-pasted (:
 prst downloadutil --pattern example --destdir ./; cd example                                                # Makes 'example' dir in current path.
 prstools prscs2 --ref ldref_1kg_pop --target target --sst sumstats.tsv --n_gwas 2565 --out ./result-prscs2 # Run the model with example data.
 prst prscs2 -r ldref_1kg_pop -t target -s sumstats.tsv -n 2565 -o ./result-prscs2 --pred                  # A shorter version of previous that also does the predictions.

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.

Tutorial

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 version of this tutorial which you can access here [Video is not available yet but will come soon]. You can load that same tutorial in a free cloud instance by clicking here: Google Colab.

Contact

For questions and support please send a mail (menno.j.witteveen@gmail.com).

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