proteome-mr-drug-target

Name: proteome-mr-drug-target
Author: GPTomics

1.1kstars185forks

How to install proteome-mr-drug-target?

gptomics/bioskills/proteome-mr-drug-target

$npx -y skills add GPTomics/bioSkills --skill proteome-mr-drug-target

Installs into the current project.

Summary

Runs cis-pQTL Mendelian randomization for drug-target validation using UKB-PPP (Olink), deCODE (SomaScan), Fenland, INTERVAL, ARIC, and FinnGen-PPP proteomes plus colocalization triangulation, phenome-wide on-target adverse-effect scans, cross-platform Olink/SomaScan replication,

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SKILL.md

1	## Version Compatibility
2
3	Reference examples tested with: TwoSampleMR 0.5.11+, MendelianRandomization 0.10+, MR-PRESSO 1.0+, coloc 5.2.3+, susieR 0.12.35+, ieugwasr 1.0+, plink2 2.00a5+, R 4.4+.
4
5	Before using code patterns, verify installed versions match. If versions differ:
6	- R: `packageVersion('<pkg>')` then `?function_name` to verify parameters
7	- CLI: `plink2 --version`; VEP `vep --help`
8
9	If code throws OAuth or rate-limit errors from OpenGWAS, or a missing `dataset$N` from coloc, introspect the installed API and adapt the example rather than retrying. UKB-PPP, deCODE, and Fenland summary statistics changed file layouts between 2023 and 2025; verify column headers before passing into `format_data()`.
10
11	# Proteome-Wide Drug-Target Mendelian Randomization
12
13	"Does genetically lowering plasma protein X cause a change in disease Y, mimicking a drug?" -> Use cis-pQTLs in the gene window for protein X as instruments under the Schmidt 2020 framework (Nat Commun 11:3255), restrict the exclusion-restriction violation to the geometric neighbourhood of the encoding gene, triangulate with colocalization (3-tier PP.H4 ladder below) and cross-platform replication (Olink vs SomaScan), and flag protein-altering-variant (PAV) confounding. A single significant cis-MR estimate is necessary but not sufficient for a drug-target claim; the operational bar is MR + coloc + cross-platform agreement + PAV-excluded sensitivity.
14
15	### PP.H4 Three-Tier Threshold Ladder
16
17	\| Tier \| PP.H4 \| Use case \|
18	\|------\|-------\|----------\|
19	\| Suggestive \| >= 0.7 \| Open Targets / exploratory; consistent with shared-causal \|
20	\| Standard publication \| >= 0.8 \| Wallace 2020 PLoS Genet 16:e1008720; most peer-reviewed pubs \|
21	\| Industry / clinical \| >= 0.95 \| Drug-claim grade; pharma internal target-validation standard \|
22
23	Operational rule: drug-target nomination requires PP.H4 >= 0.8 minimum; industry-grade clinical claim requires PP.H4 >= 0.95 plus the full triangulation panel.
24
25	- R (canonical): `TwoSampleMR::mr()` orchestrates the cis-IVW + Egger + median + Wald-ratio panel
26	- R (correlated cis-pQTLs in a window): `MendelianRandomization::mr_input(..., correlation = ld_matrix)` then `mr_ivw(mr_obj, model='default', correl = TRUE)`
27	- R (triangulation): `coloc::coloc.abf()` or `coloc::coloc.susie()` on the same cis-window
28	- pheWAS: `ieugwasr::associations()` against the OpenGWAS catalogue, looped over outcomes
29	- VEP CLI: annotate every cis-pQTL with `vep --species homo_sapiens --canonical --check_existing` for PAV flagging
30
31	## Data Source Taxonomy
32
33	\| pQTL dataset \| Platform \| N \| Proteins \| Reference \| Fails when \|
34	\|--------------\|----------\|---\|----------\|-----------\|------------\|
35	\| UKB-PPP \| Olink Explore 3072 (antibody PEA) \| 54,219 \| 2923 (54k primary cis-pQTLs across studies; 14,287 primary pQTLs across cis+trans) \| Sun 2023 Nature 622:329 \| Target not on Olink panel; ancestry mostly EUR; antibody epitope may miss isoforms \|
36	\| deCODE \| SomaScan v4 (aptamer SOMAmer) \| 35,559 \| 4907 \| Ferkingstad 2021 Nat Genet 53:1712 \| Population isolate; LD differs from outbred EUR; aptamers can be PAV-confounded \|
37	\| Fenland \| SomaScan v4 \| 10,708 \| 4775 \| Pietzner 2021 Science 374:eabj1541 \| UK Fenland-specific ascertainment; SomaScan caveats \|
38	\| INTERVAL \| SomaScan v3 (older) \| 3301 \| 3622 \| Sun 2018 Nature 558:73 \| Smaller N; older SomaScan version; useful only as replication \|
39	\| ARIC \| SomaScan v4 \| ~7000 (multi-ancestry sub-cohorts) \| 4877 \| Zhang 2022 Nat Genet 54:593 \| Stratify by ancestry; do not pool \|
40	\| FinnGen-PPP \| Olink Explore \| ~12,000 \| ~3000 \| FinnGen DF12 (2024 release) \| Finnish-specific allele frequencies; not always meta-analyse with UKB \|
41	\| AGES-Reykjavik \| SomaScan v4 \| ~5400 \| 4782 \| Emilsson 2018 Science 361:769 \| Elderly Icelandic cohort; ascertainment bias \|
42	\| Olink Explore 1536 disease-specific cohorts (CARDIoGRAMplusC4D, etc) \| Olink Explore subset \| varies \| varies \| per-study \| Lower N per cohort; use as replication \|
43
44	Methodology evolves; check the UKB-PPP portal (ukb-ppp.gwas.eu), deCODE Genetics summary-stat releases, and the eQTL Catalogue / GTEx Portal for the current data version. UKB-PPP was substantially re-released in 2024 (extended anc

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proteome-mr-drug-target

1.1kstars185forks

View on GitHub

How to install proteome-mr-drug-target?

gptomics/bioskills/proteome-mr-drug-target

$npx -y skills add GPTomics/bioSkills --skill proteome-mr-drug-target

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	## Version Compatibility
2
3	Reference examples tested with: TwoSampleMR 0.5.11+, MendelianRandomization 0.10+, MR-PRESSO 1.0+, coloc 5.2.3+, susieR 0.12.35+, ieugwasr 1.0+, plink2 2.00a5+, R 4.4+.
4
5	Before using code patterns, verify installed versions match. If versions differ:
6	- R: `packageVersion('<pkg>')` then `?function_name` to verify parameters
7	- CLI: `plink2 --version`; VEP `vep --help`
8
9	If code throws OAuth or rate-limit errors from OpenGWAS, or a missing `dataset$N` from coloc, introspect the installed API and adapt the example rather than retrying. UKB-PPP, deCODE, and Fenland summary statistics changed file layouts between 2023 and 2025; verify column headers before passing into `format_data()`.
10
11	# Proteome-Wide Drug-Target Mendelian Randomization
12
13	"Does genetically lowering plasma protein X cause a change in disease Y, mimicking a drug?" -> Use cis-pQTLs in the gene window for protein X as instruments under the Schmidt 2020 framework (Nat Commun 11:3255), restrict the exclusion-restriction violation to the geometric neighbourhood of the encoding gene, triangulate with colocalization (3-tier PP.H4 ladder below) and cross-platform replication (Olink vs SomaScan), and flag protein-altering-variant (PAV) confounding. A single significant cis-MR estimate is necessary but not sufficient for a drug-target claim; the operational bar is MR + coloc + cross-platform agreement + PAV-excluded sensitivity.
14
15	### PP.H4 Three-Tier Threshold Ladder
16
17	\| Tier \| PP.H4 \| Use case \|
18	\|------\|-------\|----------\|
19	\| Suggestive \| >= 0.7 \| Open Targets / exploratory; consistent with shared-causal \|
20	\| Standard publication \| >= 0.8 \| Wallace 2020 PLoS Genet 16:e1008720; most peer-reviewed pubs \|
21	\| Industry / clinical \| >= 0.95 \| Drug-claim grade; pharma internal target-validation standard \|
22
23	Operational rule: drug-target nomination requires PP.H4 >= 0.8 minimum; industry-grade clinical claim requires PP.H4 >= 0.95 plus the full triangulation panel.
24
25	- R (canonical): `TwoSampleMR::mr()` orchestrates the cis-IVW + Egger + median + Wald-ratio panel
26	- R (correlated cis-pQTLs in a window): `MendelianRandomization::mr_input(..., correlation = ld_matrix)` then `mr_ivw(mr_obj, model='default', correl = TRUE)`
27	- R (triangulation): `coloc::coloc.abf()` or `coloc::coloc.susie()` on the same cis-window
28	- pheWAS: `ieugwasr::associations()` against the OpenGWAS catalogue, looped over outcomes
29	- VEP CLI: annotate every cis-pQTL with `vep --species homo_sapiens --canonical --check_existing` for PAV flagging
30
31	## Data Source Taxonomy
32
33	\| pQTL dataset \| Platform \| N \| Proteins \| Reference \| Fails when \|
34	\|--------------\|----------\|---\|----------\|-----------\|------------\|
35	\| UKB-PPP \| Olink Explore 3072 (antibody PEA) \| 54,219 \| 2923 (54k primary cis-pQTLs across studies; 14,287 primary pQTLs across cis+trans) \| Sun 2023 Nature 622:329 \| Target not on Olink panel; ancestry mostly EUR; antibody epitope may miss isoforms \|
36	\| deCODE \| SomaScan v4 (aptamer SOMAmer) \| 35,559 \| 4907 \| Ferkingstad 2021 Nat Genet 53:1712 \| Population isolate; LD differs from outbred EUR; aptamers can be PAV-confounded \|
37	\| Fenland \| SomaScan v4 \| 10,708 \| 4775 \| Pietzner 2021 Science 374:eabj1541 \| UK Fenland-specific ascertainment; SomaScan caveats \|
38	\| INTERVAL \| SomaScan v3 (older) \| 3301 \| 3622 \| Sun 2018 Nature 558:73 \| Smaller N; older SomaScan version; useful only as replication \|
39	\| ARIC \| SomaScan v4 \| ~7000 (multi-ancestry sub-cohorts) \| 4877 \| Zhang 2022 Nat Genet 54:593 \| Stratify by ancestry; do not pool \|
40	\| FinnGen-PPP \| Olink Explore \| ~12,000 \| ~3000 \| FinnGen DF12 (2024 release) \| Finnish-specific allele frequencies; not always meta-analyse with UKB \|
41	\| AGES-Reykjavik \| SomaScan v4 \| ~5400 \| 4782 \| Emilsson 2018 Science 361:769 \| Elderly Icelandic cohort; ascertainment bias \|
42	\| Olink Explore 1536 disease-specific cohorts (CARDIoGRAMplusC4D, etc) \| Olink Explore subset \| varies \| varies \| per-study \| Lower N per cohort; use as replication \|
43
44	Methodology evolves; check the UKB-PPP portal (ukb-ppp.gwas.eu), deCODE Genetics summary-stat releases, and the eQTL Catalogue / GTEx Portal for the current data version. UKB-PPP was substantially re-released in 2024 (extended anc

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6 picks

Type