CREDTOOLS
CREDTOOLS is a command-line and Python toolkit for GWAS fine-mapping workflows. It helps you standardize summary statistics, define loci, prepare LD-backed locus files, run QC, combine cohorts, and run fine-mapping tools from one repeatable interface.
Documentation: https://Jianhua-Wang.github.io/credtools
What It Does
- Standardizes raw GWAS summary statistics with
credtools munge. - Finds and chunks loci from genome-wide summary statistics with
credtools chunk. - Prepares locus-level summary statistics, LD matrices, and LD maps.
- Runs meta-analysis with
meta_all,meta_by_population, orno_meta. - Offers matched geometric LD weighting with
--ld-weighting ess(default) or--ld-weighting seonmetaandpipeline. - Runs QC for LD and summary-statistic consistency.
- Runs fine-mapping with SuSiE, FINEMAP, ABF, CARMA, SuSiEx, MultiSuSiE, MESuSiE, and RSparsePro wrappers.
- Writes PIP tables, credible set summaries, causal-variant tables, logs, and plots.
Install
python -m pip install credtools
credtools --version
CREDTOOLS supports Python >=3.9,<3.13.
Some workflows need external tools:
| Workflow | Extra dependency |
|---|---|
LD extraction in chunk |
PLINK |
--tool finemap |
FINEMAP executable |
--tool susiex |
SuSiEx executable |
--tool susie_ash or susie_inf |
Rscript and susieR >= 0.16.1 |
--tool carma |
Rscript and CARMA |
--tool mesusie |
Rscript and MESuSiE |
See the external tools guide for setup checks.
Quick Start
Start from a population config:
popu cohort sample_size path ld_ref
EUR UKBB 400000 /data/EUR.sumstats.gz /ref/EUR
AFR MVP 90000 /data/AFR.sumstats.gz /ref/AFR
Run the workflow:
credtools munge population_config.tsv work/munged
credtools chunk work/munged/sumstat_info_updated.txt work/chunks
credtools pipeline work/chunks/loci_list.txt work/results \
--tool susie \
--meta-method meta_all \
--max-causal 5
Before a full run, inspect work/chunks/loci_list.txt. If chunk wrote a
placeholder sample_size or cohort label, edit it before fine-mapping.
Main Commands
| Command | Use it for |
|---|---|
credtools munge |
clean and standardize summary statistics |
credtools chunk |
find loci, create chunks, and prepare LD-backed files |
credtools prepare |
build LD-backed locus files from chunked sumstats and genotype references |
credtools meta |
combine cohorts before QC or fine-mapping |
credtools qc |
check summary-statistic and LD consistency |
credtools finemap |
run fine-mapping only |
credtools pipeline |
run meta-analysis, QC, and fine-mapping together |
credtools plot |
create QC and fine-mapping plots |
Key Input
Most downstream commands use a loci_list.txt:
locus_id chr start end popu cohort sample_size prefix
locus_1 1 50000000 50500000 EUR UKBB 400000 data/EUR_UKBB_locus_1
Each prefix should point to:
{prefix}.sumstats.gz
{prefix}.ld.npz
{prefix}.ldmap.gz
See the file schema reference for exact columns and accepted file names.
Development
git clone https://github.com/Jianhua-Wang/credtools.git
cd credtools
uv sync
uv run pytest
uv run mkdocs serve
Links
- Documentation: https://Jianhua-Wang.github.io/credtools
- GitHub: https://github.com/Jianhua-Wang/credtools
- PyPI: https://pypi.org/project/credtools/
- License: MIT
1 maintainer
Metadata
1 maintainer
Release files for credtools 0.9.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| credtools-0.9.7.tar.gz | 3.6 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| credtools-0.9.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.0 MB
Release files / credtools-0.9.7.tar.gz
| Download URL | credtools-0.9.7.tar.gz |
|---|---|
| Size | 3.6 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Uploaded via |
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Release files / credtools-0.9.7-py3-none-any.whl
| Download URL | credtools-0.9.7-py3-none-any.whl |
|---|---|
| Size | 3.4 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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