README.md

---
license: apache-2.0
tags:
  - biology
  - genomics
  - dna
  - variant-effect-prediction
  - complex-traits
  - gwas
  - fine-mapping
size_categories:
  - 10K<n<100K
---

# evals_complex_traits

Variant-effect-prediction benchmark of UKBB fine-mapped complex-trait SNVs vs
low-PIP SNVs, 1:9 matched within consequence categories on `(chrom,
consequence_final)` plus subset-targeted distance bins, with MAF entering as
a continuous matching feature.

## Description

| | |
|---|---|
| Positives | UKBB SuSiE+FINEMAP fine-mapped variants with max(PIP) > 0.9 across 119 traits |
| Negatives | max(PIP) < 0.01 across 119 traits, 1:9 matched per positive |
| Genome build | GRCh38 (lifted from hg19) |
| Variant type | SNVs only |
| Coordinates | 1-based (`pos` is 1-based; `ref`/`alt` are single bases) |
| Matching ratio | 1:9 |

## Splits

| Split | Variants (pos + 9·neg) | Positives | Chromosomes |
|---|---:|---:|---|
| `train` | 11,630 | 1,163 | odd: 1, 3, …, X |
| `test` | 10,000 | 1,000 | even: 2, 4, …, Y |
| **total** | **21,630** | **2,163** | |

## Columns

| Column | Type | Description |
|---|---|---|
| `chrom`, `pos`, `ref`, `alt` | str / int / str / str | Variant coordinates (1-based, GRCh38) |
| `label` | bool | `True` for high-PIP positive, `False` for low-PIP matched negative |
| `subset` | str | Consequence-group label for stratified eval |
| `match_group` | int | Integer ID grouping each positive with its 9 matched negatives |
| `rsid` | str | dbSNP rsID (when available) |
| `pip` | float | Maximum PIP across the 119 traits |
| `traits` | str | Comma-separated list of traits with PIP > 0.9 (positives only) |
| `MAF` | float | UKBB EUR minor allele frequency |
| `ld_score` | float | UKBB EUR LD score (passthrough, **not** a matching feature) |
| `consequence`, `consequence_cre`, `consequence_final`, `consequence_group` | str | Ensembl VEP consequence + grouping |
| `distance_tss_pc`, `distance_tss_nc`, `distance_tss` | int | Distances to nearest protein-coding / non-protein-coding TSS (and min, used for `consequence_group` recategorization) |
| `tss_closest_pc_gene_id`, `tss_closest_nc_gene_id`, `tss_closest_gene_id` | str | Ensembl gene IDs (passthrough — gene-id was *not* used in matching) |
| `distance_exon_pc`, `distance_exon_nc`, `distance_exon` | int | Same shape, for nearest exon |
| `exon_closest_pc_gene_id`, `exon_closest_nc_gene_id`, `exon_closest_gene_id` | str | Same shape |
| `distance_tss_pc_bin`, `distance_exon_pc_bin` | str | Subset-prefixed bin labels used as exact-match keys; `BIN_NA` outside the binned subsets |

## Per-subset retention

| Subset | n_pos in `dataset_all` | matched (kept) | retention |
|---|---:|---:|---:|
| `distal` | 1,193 | 1,193 | 100.0% |
| `missense_variant` | 454 | 454 | 100.0% |
| `tss_proximal` | 244 | 244 | 100.0% |
| `3_prime_UTR_variant` | 78 | 78 | 100.0% |
| `non_coding_transcript_exon_variant` | 75 | 75 | 100.0% |
| `5_prime_UTR_variant` | 56 | 56 | 100.0% |
| `synonymous_variant` | 33 | 33 | 100.0% |
| `splicing` | 30 | 30 | 100.0% |
| `mature_miRNA_variant` | 2 | 0 | 0.0% |
| **total** | **2,165** | **2,163** | **99.9%** |

## Matching design

Matching is exact on every categorical key, then Euclidean-nearest on the
(RobustScaler-scaled) continuous features as a within-group tie-breaker.
Without replacement, k=9.

- **Continuous features**: `distance_tss_pc`, `distance_tss_nc`, `distance_exon_pc`, `distance_exon_nc`, `MAF`.
- **Categorical features**:
  - `chrom`, `consequence_final`
  - `distance_tss_pc_bin` — `tss_proximal`: edges `[0, 100, 1000, ∞]`; `BIN_NA` elsewhere
  - `distance_exon_pc_bin` —
    - `tss_proximal`: edges `[0, 100, 1000, ∞]`
    - `splicing`: edges `[0, 5, 30, ∞]`
    - `BIN_NA` elsewhere

Gene-ID columns are kept as passthrough metadata but **not** used as match
keys.

## Matched-feature AUPRC diagnostic

Each continuous matching feature `f` is scored as a single-feature predictor
within each subset: `{f}_auprc = max(AP(label, +f), AP(label, −f))`.
**Baseline = 0.1 for 1:9 matching**.

<details>
<summary>Per-(subset, feature) AUPRC table</summary>

| subset | n | distance_tss_pc | distance_tss_nc | distance_exon_pc | distance_exon_nc | MAF |
|---|---:|---:|---:|---:|---:|---:|
| `distal` | 1,193 | 0.101 | 0.102 | 0.109 | 0.105 | 0.101 |
| `missense_variant` | 454 | 0.108 | 0.106 | 0.102 | 0.104 | 0.108 |
| `tss_proximal` | 244 | 0.114 | 0.114 | 0.110 | 0.108 | 0.101 |
| `3_prime_UTR_variant` | 78 | 0.119 | 0.116 | 0.108 | 0.108 | 0.114 |
| `non_coding_transcript_exon_variant` | 75 | 0.110 | 0.112 | 0.124 | 0.100 | 0.106 |
| `5_prime_UTR_variant` | 56 | 0.123 | 0.109 | 0.102 | 0.110 | 0.109 |
| `synonymous_variant` | 33 | 0.120 | 0.106 | 0.107 | 0.111 | 0.107 |
| `splicing` | 30 | 0.124 | 0.131 | 0.108 | 0.131 | 0.122 |

</details>

## Provenance

Built by the [`bolinas-dna`](https://github.com/Open-Athena/bolinas-dna) eval pipeline at commit
[`main`](https://github.com/Open-Athena/bolinas-dna/tree/main/snakemake/evals).

- Curation pipeline: [`snakemake/evals`](https://github.com/Open-Athena/bolinas-dna/tree/main/snakemake/evals)
- Matching algorithm: [`src/bolinas/pipelines/evals/matching.py`](https://github.com/Open-Athena/bolinas-dna/blob/main/src/bolinas/pipelines/evals/matching.py)
- Diagnostic helper: [`src/bolinas/pipelines/evals/matching_qc.py`](https://github.com/Open-Athena/bolinas-dna/blob/main/src/bolinas/pipelines/evals/matching_qc.py)

The curation is a from-scratch reimplementation of the [TraitGym](https://github.com/songlab-cal/TraitGym) complex-traits pipeline.

## License

Released under the same terms as its sources. UKBB summary-level data and
the [Finucane lab fine-mapping release](https://huggingface.co/datasets/gonzalobenegas/finucane-ukbb-finemapping)
are intended for non-commercial research; check upstream license if you plan
to use commercially.

## Citation

- TraitGym — Benegas *et al.* 2025, [bioRxiv 2025.02.11.637758](https://www.biorxiv.org/content/10.1101/2025.02.11.637758v2)
- UKBB fine-mapping — Wang *et al.* (Nat Commun 2021) and the [Finucane lab release](https://huggingface.co/datasets/gonzalobenegas/finucane-ukbb-finemapping)
- LD scores — Bulik-Sullivan *et al.* (Nat Genet 2015)