arcinstitute/PIE_splits

PIE: canonical splits

The train, validation and test splits of the two PIE experiments, replogle_wdataset and replogle_xdataset. The experiment configs pin this repo by commit, so pie train and pie eval download the split files they need automatically.

Datasets and knowledge sources: PIE collection

Contents

replogle_wdataset/<setting>/<cell_line>/{train,val,test}.json   setting: unseen_ctx, unseen_pert, unseen_ctx_pert
replogle_xdataset/{train,val,test_seen,test_unseen}.json

Each file is a JSON object that maps <dataset>.<context> to a list of perturbations, for example {"replogle.k562": ["AAMP", ...]}. A row is one (context, perturbation) pair of a PIE preprocessed dir. The files of one split dir are pairwise disjoint.

replogle_wdataset/

Replogle-Nadig only, four folds (hepg2, jurkat, k562, rpe1). A fold trains and validates on the other three cell lines; train.json and val.json are the same for all three settings of a fold.

Setting	Test cell lines	Test perturbations	Test rows (hepg2 / jurkat / k562 / rpe1)
unseen_ctx	held-out cell line	seen in training	867 / 978 / 884 / 983
unseen_pert	the three training lines	unseen in training	1,238 / 1,214 / 1,252 / 1,172
unseen_ctx_pert	held-out cell line	unseen in training	386 / 461 / 430 / 470

Train rows per fold: 2,670 / 2,526 / 2,603 / 2,550; validation rows: 298 / 280 / 290 / 284.

replogle_xdataset/

Trains on Tahoe, Jiang, ARC VCC 25 and Orion and tests zero-shot on the four Replogle-Nadig cell lines.

File	Contexts	Rows
train.json	tahoe 45, jiang 23, orion 2, arc_vcc_25 1	64,260
val.json	tahoe 4, jiang 2, orion 2, arc_vcc_25 1	957
test_seen.json	replogle 4 (perturbations in train.json)	2,286
test_unseen.json	replogle 4 (all other perturbations)	3,173

Usage

The experiment configs read these splits directly; pass a split file to pie eval or pie infer as an hf:// reference:

SPLITS=hf://datasets/arcinstitute/PIE_splits@396ab9563175ee887750c9eed7ccaea6f5fdbf50
uv run pie eval experiment_name=replogle_wdataset/k562 ckpt=best_auprc \
  split_path=$SPLITS/replogle_wdataset/unseen_ctx/k562/test.json row_set=unseen_ctx

To use your own splits, give a dir with train.json and val.json as data.split_dir=<dir> (local or hf://). To download the files:

hf download arcinstitute/PIE_splits --repo-type dataset --local-dir splits