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Replace the CosMx reader with a substantially expanded implementation ported from Nanostring-Biostats/spatialdata-io-ns: multi-FOV stitching, multimodal RNA+Protein, polygon<->label<->table co-registration, skip_empty_fovs, and opt-in per-channel percentile image normalization. - 5 modules: cosmx.py + _cosmx_io/_cosmx_stitching/_cosmx_discovery/_cosmx_utils - reuses the existing CosmxKeys constant - adds runtime deps: polars, dask, zarr>=3 - synthetic regression test suite (tests/test_cosmx_regression.py) Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Match the upstream reader convention: decorate cosmx() with @inject_docs and document the recognized CosMx file suffixes from CosmxKeys in the docstring.
readers/cosmx.py + the 4 _cosmx_* helper modules -> a readers/cosmx/ package (_reader/_io/_stitching/_discovery/_utils), with relative intra-package imports. No behavior change; all 86 tests pass.
The dev-era suite (82 tests) was ~2x upstream's heaviest reader test. Drop the brittle snapshot tests and the pure internal-helper unit tests (header matching, tile clipping) that are already covered end-to-end, and thin the remaining helper-unit classes to their highest-value cases. Keeps all end-to-end, feature (skip_empty_fovs, normalization, flip), and co-registration coverage. 56 tests (60 incl. parametrize), all passing.
Extract repeated boilerplate in _reader.py into small helpers, no behavior change: - _global_id_series: the AnnData unwrap + categorical->Int64 coercion (was in _collect_global_cell_ids_from_tables and _filter_tables_to_ids) - _parse_cell_table: the identical TableModel.parse(... region_key/instance_key/ overwrite_metadata) call at 3 sites - _parse_labels: the identical Labels2DModel.parse(... dims/translation) at 3 sites - _finalize_transcripts: the duplicated PointsModel.parse tail of the parquet and csv transcript readers - move the self-contained obs column-sanitization out to _utils._sanitize_obs_columns All 60 tests pass.
…hored) Make the single-modality path label-anchored, matching the multimodal path, so both follow one rule: the segmentation is the ground truth — rasterise every cell, then filter the table(s) to the cells that rasterised. Decided from real data: in multimodal runs the protein-derived segmentation is ground truth and modalities quantify DIFFERENT cell subsets (breast: RNA covers 99.1%, protein 100% of segmentation), so labels cannot be anchored on any single table. - single path: drop the table->polygon->label 'allowed_global_ids' cascade and the final-pass table filter; read_labels() rasterises all polygons, then the table is filtered to the label IDs (was: only rasterise polygons with a table row, dropping segmented-but-unquantified cells) - remove the now-dead allowed_global_ids param (read_labels/_labels_from_polygons) and _collect_global_cell_ids_from_tables - fix _prescan_max_cell_id: it read column 'cell_ID' but polygon CSVs use 'cellID', so polygon-only high cell IDs (exactly the orphan cells) were missed and mis-locked max_cell_id — now reads either column Validated on real data (breast multiomics, FOV 128): labels=649 (all polygons), RNA table=541, Protein table=649 — the 108 cells RNA lacks are kept in the labels. All 60 synthetic tests pass.
…scan A polygon cell with no expression row (highest cell_ID) must stay in the labels while the table holds only quantified cells; the high cell_ID also exercises the max_cell_id prescan reading the polygon 'cellID' column.
The pre-scan that locks max_cell_id matched the id column against a hardcoded
("cell_ID", "cellID") pair and swallowed every failure with a bare
`except: continue`. Both could silently drop a file and mis-lock the max — the
exact failure class behind the polygon-orphan mis-lock fixed in 190b121.
- Extract `_match_canonical(hdr, canon)` from `_match_header` so a single
alias table backs both; route the pre-scan's id- and fov-column lookups
through it (now also matches `cell_id`/`object_id`/`roi`/`fov_id`,
case-insensitive) instead of a narrower ad-hoc set.
- Replace the blanket silent `except` with per-step warnings: a file that
exists but can't be scanned, has no recognizable cell_ID column, or whose
max can't be read is logged and skipped — never silently dropped.
Add regression tests for aliased id/fov columns and the no-silent-drop warning.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Drop three re-implemented helpers in favour of the package/ecosystem equivalents, and attach the standard reader provenance every other reader sets. Net -50 LOC in the cosmx package; behaviour for valid inputs is unchanged (full regression suite + zarr round-trip green). - `_deduplicate_names` -> `anndata.utils.make_index_unique` for channel names (suffix format changes from "x (1)" to "x-1", the anndata standard). - `_sanitize_obs_columns` -> `spatialdata.sanitize_table`, the blessed zarr-safe key sanitiser (case-insensitive uniqueness across obs/var keys). - Add `_set_reader_metadata(sdata, "cosmx")` in `_assemble_sdata` so the output carries `spatialdata_io_reader`/`_software_version` like the other readers (cosmx previously set neither). Kept bespoke (no core equivalent): per-channel image normalization, categorical->string coercion, and the CSV-header canonicaliser. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
…safe test lookup The cosmx CLI still passed the removed transcripts= argument (TypeError on every call) and exposed none of the new reader parameters; expose all of them (test_cli_alignment). The co-registration test helper put a -1 sentinel into a uint16 label lookup, which NumPy 2 rejects (OverflowError).
…d best-effort excepts)
…the max-cell_ID pre-scan
AtoMx metadata files carry both cell_id ('c_1_51_1') and cell_ID (the per-FOV integer); the
case-insensitive alias matched cell_id first and the pre-scan crashed on int('c_1_51_999') for every
public AtoMx export. An exact canonical column now wins over the aliases, and a non-integer max is
skipped with a warning.
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AtoMx exports add a string `cell` column after cell_ID, and R-exported GEO
files put rownames, sampleID, slide and case before fov. All of them went
into X ("scipy.sparse does not support dtype object"). Genes are now the
numeric columns after cell_ID. Other columns go to obs, as strings, and
are kept when the metadata file replaces obs. The empty R rowname column
is dropped.
Its gene columns became zarr keys, and multi-gene probe names such as Gstp1/2 are not valid keys, so writing the SpatialData failed. varm holds it as genes x FOVs (columns fov_<id>), aligned with var.
…oordinates Some GEO exports key cells only by c_<slide>_<fov>_<cell> (exprMat `cell_id`, string metadata `cell_ID`, no fov column). Parse fov and the integer cell_ID from it, keep the string as `cell`, and fail on ids that fit neither form. When the FOV positions file has no pixel or mm coordinates, read the cell tables only and warn: nothing per-FOV can be placed, and cell positions stay in the metadata columns.
Set it before sanitize_table so varm follows any var renaming, and raise if a table gene has no background value.
…'s cell ids Some metadata files have no cell_ID column, only the c_<slide>_<fov>_<cell> string in `cell` (GSE305393): derive cell_ID from it. The transcripts file can assign transcripts to a cell id above every polygon/exprMat row (GSE304160: 2755 vs 2754), which broke the max_cell_id lock: include it in the pre-scan when transcripts are read.
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Summary
This replaces the CosMx reader with a substantially expanded implementation developed in
Nanostring-Biostats/spatialdata-io-ns. The current reader (~280 lines, single file) is replaced by a 5-module reader (~3.8k lines) that adds:global_cell_idacross elements).skip_empty_fovs— drops phantom FOVs listed in the positions file but absent on disk (avoids an inflated/desynced canvas).image_normalization_percentile, defaultNone= legacy dtype-max) — recovers low-signal uint16 channels that otherwise render near-black; scale-only and reversible.CellStatsDir, px-only / mm-only / px+mm FOV positions).Reuses the existing
CosmxKeysconstant (values unchanged). Adds runtime depspolars,dask,zarr>=3. Other readers are untouched.The public
cosmx()signature changes:transcripts=Trueread_transcripts=True(+read_images/labels/proteins/polygons/gexp)imread_kwargs: Mapping = MappingProxyType({})imread_kwargs: dict | None = Noneimage_models_kwargs: Mapping = MappingProxyType({})image_models_kwargs: dict | None = Nonefovs,channels,n_workers,flip_image,image_normalization_percentile,polygons_as_labels,keep_polygons_after_rasterize,align_rasters_to_polygons,add_fovs_as_shapes,skip_empty_fovs,preview_fovsNew public objects:
CosMxDataset(frozen dataclass describing the on-disk layout) andCosMxDatasetReader.