--- license: cc-by-nc-4.0 pretty_name: Z-Screen Source Data (June 2026 Release) tags: - drug-discovery - single-cell - transcriptomics - high-content-imaging - cheminformatics - perturbation size_categories: - 100K On the Zenodo record, each top-level folder above is provided as a single `.zip` > (`raw_counts_data.zip` is 4.0 GB, MD5 `796235d30c4e7e821fe8453f07afae45`). On Hugging Face the > same files are provided uncompressed for direct/streamed access. ### `normalized_image_embeddings/` (~6 MB) | File | Shape | Description | |---|---|---| | `normalized_image_embeddings.parquet` | 21,795 x 39 | Compound-level normalized morphology (image) features, keyed by `public_compound_id`. | | `biomarker_intensity_layer.parquet` | 18,942 x 11 | Protein/cellular-state marker intensities (BRD4, p21/CDKN1A, DAPI, actin, ConA, p62/SQSTM1). | ### `chemical_features/` (~295 MB) | File | Shape | Description | |---|---|---| | `compound_chemistry_feature_master.parquet` | 144,645 x 961 | Compound + building-block chemistry, keyed by `public_compound_id`. Formula/InChIKey where available, plus Chemeleon and ChemBERTa embeddings (whole-molecule and per-building-block BB0 to BB4). | ### `active_seq_same_well/` (~440 MB) The public layer supporting the claim that RNA and morphology were measured from the **same physical nanowell**. The primary deliverable is self-contained; the remaining files are the full pre-join latent spaces so the same-well matching can be reproduced from scratch. | File | Shape | Role | |---|---|---| | `joined_same_well_data_with_public_compound_id.parquet` | 18,727 x 550 | **Primary deliverable.** Matched same-well rows carrying 32 RNA latent dims (`D00`-`D31`), 448 image latent dims (`img_lat_*`), well geometry, RNA QC, and public compound mapping. | | `activeseq_control_name_public_compound_map.parquet` | 36 x 7 | Control-name to `public_compound_id` mapping (35 named compounds, 2 ActiveSeq devices). | | `imaging_lats.parquet` | 126,662 x 451 | Full imaging-patch latent space (pre-join). | | `rnaseq_lats.parquet` | 61,101 x 33 | Full RNA-cell latent space (pre-join). | | `assay_well_dataframe.parquet` | 126,662 x 35 | Imaging-patch geometry / detection metadata. | | `rnaseq_obs.parquet` | 61,101 x 27 | RNA-cell observation metadata / QC. | | `matches_table.parquet` | 20,222 x 8 | Imaging-to-RNA well matches used to build the joined table. | > Note: the redundant `joined_same_well_data.parquet` (a strict subset of the > `_with_public_compound_id` table, differing only by a pandas index column) is intentionally > excluded from this deposit. ### `external_reference/` (~182 MB) Clean, reusable external-benchmark surface. The core assets are the **ranked gene-list signature tables** (`*_rank_signatures_top_genes.parquet`) plus their metadata, catalogs, provenance, and gene sets. | Atlas | Key ranked-gene-list table | |---|---| | Replogle 2022 K562 genome-wide CRISPR KO | `crispr_perturbation_atlases/replogle_2022_k562_gwps/replogle_rank_signatures_top_genes.parquet` | | Replogle 2022 RPE1 CRISPR KO | `crispr_perturbation_atlases/replogle_2022_rpe1/rpe1_rank_signatures_top_genes.parquet` | | Norman & Weissman 2019 K562 CRISPRa | `crispr_perturbation_atlases/norman_weissman_2019_k562_crispra/norman_rank_signatures_top_genes.parquet` | | Selected THP1 scPerturb CRISPR | `crispr_perturbation_atlases/scperturb_thp1_selected/scperturb_rank_signatures_top_genes.parquet` | | LINCS L1000 compound signatures | `compound_atlases/lincs_l1000/processed/lincs_l1000_rank_signatures_top_genes.parquet` | | Tahoe-100M | `compound_atlases/tahoe_100m/` (metadata + capmatinib slice) | | Control transcriptome expansion (2026-05-25) | `compound_atlases/control_transcriptome_expansion_20260525/` | Also included: `benchmark_outputs/` (prior LINCS vs Z-Screen overlap/correlation outputs), `catalog/` (dataset catalog, file manifest with hashes, provenance), `gene_sets/` (Enrichr KEGG / Hallmark / Reactome GMTs, disease-reversal and aging signature JSONs), and the provenance/fetch scripts documenting how the tables were produced. > Curation note: the raw external `.h5ad` matrices (`scperturb_downloads/`, ~6.3 GB) are **not** > bundled here. They are publicly re-downloadable from scPerturb's own Zenodo record; see > `crispr_perturbation_atlases/scperturb_thp1_selected/source_manifest/` and > `external_reference/fetch_zenodo.py` for retrieval. Only the processed rank-signature tables are > included, so downstream comparisons do not require rebuilding them. ## Loading Parquet (Python): ```python import pandas as pd master = pd.read_parquet("raw_counts_data/MasterFile.parquet") chem = pd.read_parquet("chemical_features/compound_chemistry_feature_master.parquet") # link biology to chemistry on the shared key merged = master.merge(chem, on="public_compound_id", how="left") ``` Counts (AnnData): ```python import anndata as ad adata = ad.read_h5ad("raw_counts_data/counts.h5ad") # 768,162 obs (nanowells) x 46,944 vars (genes) ``` Hugging Face `datasets` (streaming, no full download) - the main parquet tables are exposed as named configs for the dataset viewer and `load_dataset`: ```python from datasets import load_dataset ds = load_dataset("Zafrens/zscreen_pilot_data", "master_well_table", split="train", streaming=True) print(next(iter(ds))) ``` Available configs: `master_well_table`, `chemical_features`, `image_embeddings`, `biomarker_intensity`, `same_well_rna_image`, `activeseq_compound_map`, `ref_replogle_k562`, `ref_replogle_rpe1`, `ref_norman_k562`, `ref_scperturb_thp1`, `ref_lincs_l1000`. The `counts.h5ad` matrix is not exposed to the viewer (load it with AnnData as shown above); all other files remain directly downloadable. ## Data fields Key columns of the headline tables (`public_compound_id` is the shared join key across all layers). **`master_well_table`** (`raw_counts_data/MasterFile.parquet`, 768,162 x 274) - one row per nanowell, aligned 1-to-1 with `counts.h5ad`: - Identifiers: `obs_id`, `device_id`, `sample_id`, `cell_line`, `zlibrary`, `condition_role` - Compound / chemistry: `public_compound_id` (+ `_source`), `public_bb0_id`..`public_bb4_id`, `chemistry_grain`, `name`, `molecular_formula`, `inchi_key` - Chemistry embedding: `whole_chemeleon_chemeleon_proj_000`..`_NNN` (whole-molecule Chemeleon projection) **`chemical_features`** (144,645 x 961) - one row per `public_compound_id`: - Support / provenance: `source_*`, `condition_*`, `token_single_*`, `token_all_*`, `public_primary_bb0_id`..`bb4_id`, `molecular_formula`, `inchi_key` - Embeddings: whole-molecule Chemeleon and ChemBERTa feature blocks, plus per-building-block Chemeleon blocks for BB0 through BB4 **`image_embeddings`** (21,795 x 39) - compound-level morphology: - Keys: `aggregate_id`, `public_compound_id`, `zlibrary`, `image_dataset`, `is_control`, `cell_line_context`, `public_condition_level_mrna_join_key` - Features: `pca_00`..`pca_31` (32 principal-component image features) **`biomarker_intensity`** (18,942 x 11) - marker-state intensities (`*_channel_masked_mean_zrobust_mean`): `BRD4_anti_target_curated`, `CDKN1A_p21`, `DAPI`, `PHALLOIDIN_ACTIN`, `CONCANAVALIN_A`, `SQSTM1_p62`. **`same_well_rna_image`** (`joined_same_well_data_with_public_compound_id.parquet`, 18,727 x 550) - matched same-nanowell rows: `D00`..`D31` (32 RNA latent dims), `img_lat_*` (448 image latent dims), well geometry, RNA QC metrics, and the public compound mapping columns. **`ref_*` tables** - external ranked gene-list signatures; each row is a (signature, gene) rank entry used for gene-rank / phenomimic comparison. Treat a high similarity as a perturbation-state hypothesis, not direct target identification. ## Integrity `MANIFEST.csv` lists every file with its SHA256 checksum, byte size, and (for parquet) row and column counts. Verify a download with, for example, `sha256sum -c` after reformatting, or by recomputing hashes and comparing against the manifest. ## Excluded from this release The following were deliberately left out of the deposit: the `Manuscripts_June2026` folder, the `zscreen_v2` / `v3` / `v4` working directories, the raw external `scperturb_downloads/` H5AD matrices, and the redundant `active_seq_same_well/joined_same_well_data.parquet`. ## License and citation License: **CC BY-NC 4.0** (Creative Commons Attribution-NonCommercial 4.0 International). You may share and adapt the data with attribution, for non-commercial purposes only. This dataset is archived on Zenodo. Cite the **concept DOI**, which always resolves to the latest version: **[10.5281/zenodo.21195738](https://doi.org/10.5281/zenodo.21195738)**. To pin the exact files of a specific release for reproducibility, use that release's version DOI instead (v1, `2026.06` = `10.5281/zenodo.21195739`). Please also cite the associated Z-Screen manuscript once available. ```bibtex @dataset{vijayan_zscreen_2026, author = {Vijayan, Swamy}, title = {{Z-Screen Source Data: single-nanowell transcriptomics, image embeddings, and compound chemistry}}, year = {2026}, publisher = {Zenodo}, doi = {10.5281/zenodo.21195738}, url = {https://doi.org/10.5281/zenodo.21195738} } ```