---
license: mit
language:
- en
- zh
tags:
- genomics
- msa
- variant-effect-prediction
- zarr
---

# pevo-msa-grch38-19way (dataset Hub)

**EN:** Training data, thesis tables, and reproduction artifacts for primate MSA variant-effect modeling.  
**中文：** 灵长类 MSA 变异效应建模的**训练数据**与**论文复现数据**（不含模型权重）。

| | |
| --- | --- |
| **Code & experiment map** | [github.com/jasperyeoh/pevo-msa-primate-genomics](https://github.com/jasperyeoh/pevo-msa-primate-genomics) — see `EXPERIMENT_MAP.md` |
| **Model checkpoints** | [jasperyeoh2/pevo-msa-mlm-19way](https://huggingface.co/jasperyeoh2/pevo-msa-mlm-19way) |
| **Full file tree** | `docs/HUGGINGFACE_DATASET_LAYOUT.md` (this repo) |
| **Upload audit** | `docs/UPLOAD_AUDIT.md` on GitHub |

---

## Dataset vs model — which Hub?

```text
  GitHub (code + small CSV)          THIS REPO (data)              MODEL REPO (weights)
  ─────────────────────────          ────────────────              ────────────────────
  scripts, configs, thesis CSV  →    Zarr, MAF, thesis_repro  +    base_models/*/checkpoint-best
                                     windows, conservation          configs/, inventory/
```

---

## Quick download / 快速下载

```bash
pip install -U huggingface_hub

# A) Paper reproduction only (~hundreds of MB)
hf download jasperyeoh2/pevo-msa-grch38-19way --repo-type dataset --local-dir data_hf \
  --include 'thesis_repro/**' 'docs/**'

# B) Training corpus (Zarr per-chromosome tar — extract after download)
hf download jasperyeoh2/pevo-msa-grch38-19way --repo-type dataset --local-dir data_hf \
  --include 'new_dataset_27feb/msaasr_dataset_10primates_full/**'

# C) Full snapshot (100GB+)
hf download jasperyeoh2/pevo-msa-grch38-19way --repo-type dataset --local-dir data_hf
```

---

## `thesis_repro/` — paper tables & scores

Restore into a Git clone (paths expected by `thesis_manu_v2_6/scripts/`):

```bash
git clone https://github.com/jasperyeoh/pevo-msa-primate-genomics.git
cd pevo-msa-primate-genomics
hf download jasperyeoh2/pevo-msa-grch38-19way --repo-type dataset --local-dir ../data_hf \
  --include 'thesis_repro/**'

mkdir -p phylo_msa1/outputs/vep_all_base_models
cp ../data_hf/thesis_repro/phylo_msa1_outputs/VEP_*.csv phylo_msa1/outputs/
cp ../data_hf/thesis_repro/phylo_msa1_outputs/vep_all_base_models/*.parquet \
   phylo_msa1/outputs/vep_all_base_models/

cp -a ../data_hf/thesis_repro/dna_foundation_benchmark_results_final \
      downstream_tasks/dna_foundation_benchmark/results_final

mkdir -p thesis_manu_v2_6/artifacts
cp ../data_hf/thesis_repro/thesis_manu_v2_6_artifacts/* thesis_manu_v2_6/artifacts/
```

**Tip:** Many **summary CSVs** are also on GitHub now — `git clone` alone is enough for Tier-A LaTeX regeneration (see `EXPERIMENT_MAP.md`).

| `thesis_repro/` path | Used for |
| --- | --- |
| `phylo_msa1_outputs/VEP_*.csv` | VEP leaderboards, strict-v2 tables (`tab:vep_*`, `tab:strictv2_*`) |
| `phylo_msa1_outputs/vep_all_base_models/*.parquet` | Per-checkpoint VEP vectors, ablation registry |
| `dna_foundation_benchmark_results_final/` | Feng AUROC tables/figures (`tab:feng_*`, `fig:feng_*`) |
| `thesis_manu_v2_6_artifacts/` | Matched-width strict-v2 bootstrap (May 2026) |

---

## Main data prefixes / 主要数据目录

| Prefix | Contents | Size |
| --- | --- | --- |
| `thesis_repro/` | Paper CSV + VEP parquets + Feng summaries | small |
| `new_dataset_27feb/msaasr_dataset_10primates_full/bundles/` | 24× `msaasr.zarr.bundle_*.tar` | ~132 GB total |
| `new_dataset_27feb/gpnmsa_1024bp_pipeline/` | 1024bp window parquets, VEP ablation (VCFs may be chunked) | mixed |
| `window_workspace/neutral_model_10primates/` | `merged_10primates_training.maf` | ~23 GB |
| `conservation_pipeline/scores/` | phastCons / phyloP `.wig` per chromosome | moderate |
| Root `train_*.parquet`, `windows_10primates_*.parquet` | Multi-resolution window panels | moderate each |
| `msaasr.zarr/` (legacy) | Old chunk tree at repo root | prefer **bundles** |

---

## Thesis figure/table index (data side)

| LaTeX label | Data on this Hub |
| --- | --- |
| `tab:vep_*`, `tab:strictv2_*`, `tab:vep_leaderboard_full` | `thesis_repro/phylo_msa1_outputs/VEP_*.csv` (+ parquets) |
| `fig:feng_*`, `tab:feng_*` | `thesis_repro/dna_foundation_benchmark_results_final/` |
| `fig:gnomad-tail-*` | CSV on **GitHub**; score parquets cluster-only |
| Retrain from scratch | `bundles/*.tar` → extract `msaasr.zarr/` |

Checkpoints for scoring: **model Hub** `base_models/full_training_*/checkpoint-best/`.  
Full mapping: GitHub `EXPERIMENT_MAP.md`.

---

## MSAASR Zarr restore / 训练语料恢复

1. Download `new_dataset_27feb/msaasr_dataset_10primates_full/bundles/msaasr.zarr.bundle_*.tar`
2. Read `README_MSAASR_BUNDLES.md` in that folder
3. Extract to `new_dataset_27feb/msaasr_dataset_10primates_full/msaasr.zarr/`
4. Do **not** rely on root `msaasr.zarr/` chunk trees (millions of files; slow)

---

## Regenerate thesis LaTeX (minimal)

```bash
cd pevo-msa-primate-genomics/thesis_manu_v2_6/scripts
python3 gen_strictv2_ci_artifacts.py
python3 gen_feng_combined_seq_and_l7_auroc.py
cd .. && latexmk -pdf main.tex
```

---

## Citation & license

Cite the thesis/preprint and pin this dataset commit from **History**.  
License: MIT (dataset card). gnomAD / ClinVar / EPO data remain under their original terms.