This mini-protocol selects among univariate, multivariate, multigene, functional and summary-statistic fine-mapping routes according to the available data and analysis goal.
Miniprotocol Timing¶
Timing: TBD
Overview¶
The MNM regression module analyzes individual-level genotype and molecular-phenotype data. qtl_dataset_construct+susie_twas performs univariate SuSiE fine-mapping and estimates TWAS weights; mnm jointly analyzes multiple molecular traits with multivariate priors; mnm_genes extends the multivariate model across genes; and fsusie fine-maps functional or epigenomic phenotypes.
The RSS module instead combines GWAS summary statistics with an external LD reference. These five commands are alternative analysis routes rather than a mandatory chain.
Steps¶
| Analysis goal | Commands to run, in order | Inputs |
|---|---|---|
| Univariate molecular-QTL fine-mapping and TWAS weights | 1 | Genotype BED set, phenotype manifest, covariates and association windows under input/colocboost/ |
| Multivariate fine-mapping across molecular traits | 2 | Step 1 inputs plus tests/fixtures/qtl_mini/fine_mapping_meta.tsv |
| Multigene multivariate fine-mapping | 3 | Multivariate inputs plus phenotype-ID map and retained-sample list under input/colocboost/ |
| Fine-map functional or epigenomic phenotypes | 4 | tests/fixtures/qtl_mini/protocol_example.genotype.chr22.bed; phenotype manifest, covariates and windows |
| GWAS summary-statistic fine-mapping | 5 | tests/fixtures/rss_analysis/protocol_example.rss_mwe.gwas_meta.tsv; tests/fixtures/ld_reference/ld_meta_file.tsv |
Run only the command matching the analysis goal.
1. Univariate fine-mapping and TWAS¶
What it does: qtl_dataset_construct+susie_twas builds the regional dataset, fits SuSiE and saves fine-mapping results and cross-validated TWAS weights.
sos run pipeline/mnm_regression.ipynb qtl_dataset_construct+susie_twas --name protocol_example --cwd output/mnm/univariate --genoFile tests/fixtures/qtl_mini/protocol_example.genotype.chr22.bed --phenoFile tests/fixtures/qtl_mini/protocol_example.pheno_manifest_context.tsv --covFile tests/fixtures/qtl_mini/example_covariates.tsv --customized-association-windows tests/fixtures/qtl_mini/association_windows.bed --region-name ENSG00000130538 --transpose-covariates --save-data -j12. Multivariate fine-mapping¶
What it does: mnm jointly fine-maps multiple molecular traits using the analyses and prior settings specified by the fine-mapping metadata.
sos run pipeline/mnm_regression.ipynb mnm --name protocol_example --cwd output/mnm/multivariate --genoFile tests/fixtures/qtl_mini/protocol_example.genotype.chr22.bed --phenoFile tests/fixtures/qtl_mini/protocol_example.pheno_manifest_context.tsv --covFile tests/fixtures/qtl_mini/example_covariates.tsv --customized-association-windows tests/fixtures/qtl_mini/association_windows.bed --fine-mapping-meta tests/fixtures/qtl_mini/fine_mapping_meta.tsv --transpose-covariates --save-data -j13. Multigene multivariate fine-mapping¶
What it does: mnm_genes coordinates multivariate fine-mapping across genes while preserving phenotype identifiers and a common retained-sample set.
sos run pipeline/mnm_regression.ipynb mnm_genes --name protocol_example --cwd output/mnm/multigene --genoFile tests/fixtures/qtl_mini/protocol_example.genotype.chr22.bed --phenoFile tests/fixtures/qtl_mini/protocol_example.pheno_manifest_context.tsv --covFile tests/fixtures/qtl_mini/example_covariates.tsv --customized-association-windows tests/fixtures/qtl_mini/association_windows.bed --pheno-id-map-file tests/fixtures/qtl_mini/pheno_id_map.tsv --fine-mapping-meta tests/fixtures/qtl_mini/fine_mapping_meta.tsv --keep-samples tests/fixtures/qtl_mini/keep_samples.txt --save-data -j14. Functional fine-mapping¶
What it does: fsusie applies functional SuSiE to epigenomic or other functional phenotypes and saves posterior fine-mapping results and residual data.
sos run pipeline/mnm_regression.ipynb fsusie --name protocol_example --cwd output/mnm/fsusie --genoFile tests/fixtures/qtl_mini/protocol_example.genotype.chr22.bed --phenoFile tests/fixtures/qtl_mini/pheno_manifest.tsv --covFile tests/fixtures/covariate_hidden_factor/covariates.tsv --customized-association-windows tests/fixtures/qtl_mini/association_windows.bed --cis-window 0 --max-cv-variants 5000 --save-data -j15. Summary-statistic fine-mapping¶
What it does: the RSS chain harmonizes regional GWAS summary statistics with the LD reference, runs SuSiE-RSS fine-mapping and produces a regional diagnostic plot.
sos run pipeline/rss_analysis.ipynb generate_manifest+generate_gwas_sumstats+gwas_fine_mapping+gwas_rss_plot --cwd output/mnm/rss --modular-script-dir code/script --gwas-meta tests/fixtures/rss_analysis/protocol_example.rss_mwe.gwas_meta.tsv --regions chr22:49355984-50799822 --ld-meta tests/fixtures/ld_reference/ld_meta_file.tsvOutput¶
| Route | Output filename and relative path | Description |
|---|---|---|
| Univariate | output/mnm/univariate/**/*.univariate_bvsr.rds; output/mnm/univariate/**/*.twas_weights.rds | SuSiE posterior and TWAS-weight objects |
| Multivariate | output/mnm/multivariate/**/*.multivariate_bvsr.rds; output/mnm/multivariate/**/*.twas_weights.rds | Joint multivariate posterior and weights |
| Multigene | output/mnm/multigene/**/* | Per-region, per-gene multivariate results and metadata |
| Functional | output/mnm/fsusie/**/*.fsusie.rds; saved residual objects | Functional fine-mapping posterior and residual data |
| RSS | output/mnm/rss/fine_mapping/AD_Bellenguez_2022.chr22_49355984_50799822.gwas_finemap.rds; regional plot under output/mnm/rss/plots/ | Summary-statistic fine-mapping result and diagnostic plot |
Anticipated Results¶
Each route produces posterior inclusion probabilities and credible-set information for the selected region and analysis model. Routes that estimate prediction weights also save TWAS-weight objects. The RSS route additionally records the harmonized regional summary statistics and LD-based diagnostics.
Command Interface¶
sos run pipeline/mnm_regression.ipynb -hsos run pipeline/rss_analysis.ipynb -h