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Dev #45

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merged 14 commits into from
Oct 27, 2024
Merged

Dev #45

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e1b9a43
update threshold to 0.95, and add time testing function
zeyunlu Sep 2, 2024
316b4a9
update documentation
zeyunlu Sep 2, 2024
de42aef
fix small bugs
zeyunlu Sep 10, 2024
c25ebb2
improve codes
zeyunlu Sep 13, 2024
15a0d9f
enhance codes and addd summary version
zeyunlu Sep 18, 2024
2f161f4
fix bugs
zeyunlu Sep 18, 2024
ce9ccea
fix bugs
zeyunlu Sep 19, 2024
e8cd972
fix bugs
zeyunlu Sep 19, 2024
2e392cf
add time checker function
zeyunlu Sep 21, 2024
943b0b4
fix typos
zeyunlu Sep 21, 2024
6a1f545
enhance qc codes
zeyunlu Oct 17, 2024
f99a4ea
add cli for summary-level data fine-mapping
zeyunlu Oct 25, 2024
cf23d72
fix typo
zeyunlu Oct 25, 2024
3b212a1
fix typos
zeyunlu Oct 27, 2024
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2 changes: 2 additions & 0 deletions .gitignore
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Expand Up @@ -4,6 +4,8 @@
# Development-specific
__pycache__/

.vscode/

*.metadata2.mmm
test_result*
*.sh
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30 changes: 20 additions & 10 deletions README.md
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Expand Up @@ -49,11 +49,18 @@ software versions of the other projects.

SuShiE software is very easy to use:

For fine-mapping using individual-level data:
``` bash
cd ./data/
sushie finemap --pheno EUR.pheno AFR.pheno --vcf vcf/EUR.vcf vcf/AFR.vcf --covar EUR.covar AFR.covar --output ./test_result
```

For fine-mapping using summary-level data:
``` bash
cd ./data/
sushie finemap --summary --gwas EUR.gwas AFR.gwas --vcf vcf/EUR.vcf vcf/AFR.vcf --sample-size 489 639 --gwas-header chrom snp pos a1 a0 zs --output ./test_result
```

It can perform:

- SuShiE: multi-ancestry fine-mapping accounting for ancestral
Expand All @@ -63,33 +70,36 @@ It can perform:
correlation
- Meta-SuSiE: single-ancestry SuSiE followed by meta-analysis
- Mega-SuSiE: single-ancestry SuSiE on row-wise stacked data across
ancestries
- QTL effect size correlation estimation
- cis-SNP heritability estimation
- Cross-validation for SuShiE prediction weights
ancestries (individual-level data only)
- *cis*-molQTL effect size correlation estimation
- *cis*-SNP heritability estimation (individual-level data only)
- Cross-validation for SuShiE prediction weights (individual-level data only)
- Convert prediction results to
[FUSION](http://gusevlab.org/projects/fusion/) format, thus can be
used in [TWAS](https://www.nature.com/articles/ng.3506)
used in [TWAS](https://www.nature.com/articles/ng.3506) (individual-level data only)

See [here](https://mancusolab.github.io/sushie/) for more details on how
to use SuShiE.

If you want to use in-software SuShiE inference function, you can use
following code as an example:
following Python code as an example:

``` python
from sushie.infer import infer_sushie
# Xs is for genotype data, and it should be a list of numpy array whose length is the number of ancestry.
# ys is for phenotype data, and it should also be a list of numpy array whose length is the number of ancestry.
infer_sushie(Xs=X, ys=y)
# Or summary-level data
# lds is for LD data, and it should be a list of p by p numpy array whose length is the number of ancestry.
# zs is for GWAS data, and it should be a list of numpy array whose length is the number of ancestry/
infer_sushie_ss(lds=LD, zs=GWAS, ns=np.array([100, 100]))
```

You can play it with your own ideas!
You can customize this function with your own ideas!

## Notes

- SuShiE currently only supports **continuous** phenotype fine-mapping.
- SuShiE currently only supports fine-mapping on autosomes.
- SuShiE currently only supports **continuous** phenotype fine-mapping for individual-level data.
- SuShiE uses [JAX](https://github.com/google/jax) with [Just In
Time](https://jax.readthedocs.io/en/latest/jax-101/02-jitting.html)
compilation to achieve high-speed computation. However, there are
Expand All @@ -108,7 +118,7 @@ You can play it with your own ideas!
| 0.13 | Add `--keep` command to enable user to specify a file that contains the subjects ID SuShiE will perform on. Add `--ancestry_index` command to enable user to specify a file that contains the ancestry index for fine-mapping. With this, user can input single phenotype, genotype, and covariate file that contains all the subjects across ancestries. Implement padding to increase inference time. Record elbo at each iteration and can access it in the `infer.SuShiEResult` object. The alphas table now outputs the average purity and KL divergence for each `L`. Change `--kl_threshold` to `--divergence`. Add `--maf` command to remove SNPs that less than minor allele frequency threshold within each ancestry. Add `--max_select` command to randomly select maximum number of SNPs to compute purity to avoid unnecessary memory spending. Add a QC function to remove duplicated SNPs. |
| 0.14 | Remove KL-Divergence pruning. Enhance command line appearance and improve the output files contents. Fix small bugs on multivariate KL. |
| 0.15 | Fix several typos; add a sanity check on reading vcf genotype data by assigning gt_types==Unknown as NA; Add preprint information. |
| 0.16 | Add option to remove ambiguous SNPs; fix several bugs and enhance codes quality. |
| 0.16 | Implement summary-level data inference. Add option to remove ambiguous SNPs; fix several bugs and enhance codes quality. |

## Support

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