Add reader for DIA-NN report.parquet format

README.rst

@@ -92,6 +92,7 @@ Supported file formats
  `AlphaDIA precursors TSV <https://alphadia.readthedocs.io/en/latest/quickstart.html#output-files>`_                   ``alphadia``             ✅              ❌
  `CBOR <https://psm-utils.readthedocs.io/en/stable/api/psm_utils.io#module-psm_utils.io.cbor>`_                        ``cbor``                 ✅              ✅                Requires the optional ``cbor2`` dependency (``pip install psm-utils[cbor]``)
  `DIA-NN TSV <https://github.com/vdemichev/DiaNN#output>`_                                                             ``diann``                ✅              ❌
+ `DIA-NN report.parquet <https://github.com/vdemichev/DiaNN#output>`_                                                  ``diann_parquet``        ✅              ❌
  `FlashLFQ generic TSV <https://github.com/smith-chem-wisc/FlashLFQ/wiki/Identification-Input-Formats>`_               ``flashlfq``             ✅              ✅
  `FragPipe PSM TSV <https://fragpipe.nesvilab.org/docs/tutorial_fragpipe_outputs.html#psmtsv/>`_                       ``fragpipe``             ✅              ❌
  `ionbot CSV <https://ionbot.cloud/>`_                                                                                 ``ionbot``               ✅              ❌

psm_utils/io/__init__.py

@@ -182,6 +182,12 @@ class FileType(TypedDict):
         "extension": ".tsv",
         "filename_pattern": r"^.*(?:_|\.)?diann\.tsv$",
     },
+    "diann_parquet": {
+        "reader": diann.DIANNParquetReader,
+        "writer": None,
+        "extension": ".parquet",
+        "filename_pattern": r"^.*(?:_|\.)?report\.parquet$",
+    },
     "parquet": {  # List after more specific Parquet patterns to avoid matching conflicts
         "reader": parquet.ParquetReader,
         "writer": parquet.ParquetWriter,

psm_utils/io/diann.py

@@ -2,14 +2,20 @@
 Reader for PSM files from DIA-NN.
 
 Reads the '.tsv' file as defined on the
-`DIA-NN documentation page <https://github.com/vdemichev/DiaNN/tree/1.8.1?tab=readme-ov-file#main-output-reference>`_.
+`DIA-NN documentation page <https://github.com/vdemichev/DiaNN/tree/1.8.1?tab=readme-ov-file#main-output-reference>`_,
+or the ``report.parquet`` main report written by DIA-NN 2.0 and later.
 
 Notes
 -----
 - DIA-NN calculates q-values at both the run and library level. The run-level q-value is used as
   the PSM q-value.
-- DIA-NN currently does not return precursor m/z values.
 - DIA-NN currently does not support C-terminal modifications in its searches.
+- The classic ``.tsv`` main report does not contain precursor m/z values or decoy status; these
+  are set to ``None``/``False``, respectively. The ``report.parquet`` main report does contain
+  both, and they are used when available.
+- The ``report.parquet`` main report does not contain a PSM-level score (no ``CScore`` column)
+  or an MS2 scan number (no ``MS2.Scan`` column). The score is set to ``None`` and
+  ``Precursor.Id`` is used as the spectrum identifier instead.
 
 """
 
@@ -22,6 +28,7 @@
 from typing import Any, cast
 
 import pandas as pd
+import pyarrow.parquet as pq  # type: ignore[import]
 
 from psm_utils.io._base_classes import ReaderBase
 from psm_utils.io._utils import set_csv_field_size_limit
@@ -90,11 +97,11 @@ def _get_peptide_spectrum_match(
             run=psm_dict["Run"],
             is_decoy=False,
             qvalue=psm_dict["Q.Value"],
-            pep=float(psm_dict["PEP"]),
-            score=float(psm_dict["CScore"]),
+            pep=psm_dict["PEP"],
+            score=psm_dict["CScore"],
             precursor_mz=None,  # Not returned by DIA-NN :(
-            retention_time=float(psm_dict["RT"]),
-            ion_mobility=float(psm_dict["IM"]),
+            retention_time=psm_dict["RT"],
+            ion_mobility=psm_dict["IM"],
             protein_list=psm_dict["Protein.Ids"].split(";"),
             source="diann",
             rank=None,
@@ -130,3 +137,69 @@ def from_dataframe(cls, dataframe: pd.DataFrame) -> PSMList:
         """Create a PSMList from a DIA-NN Pandas DataFrame."""
         records = cast(list[dict[str, str]], dataframe.to_dict(orient="records"))
         return PSMList(psm_list=[cls._get_peptide_spectrum_match(entry) for entry in records])
+
+
+class DIANNParquetReader(ReaderBase):
+    """Reader for the DIA-NN 2.0+ ``report.parquet`` main report."""
+
+    def __init__(self, filename: str | Path, *args: Any, **kwargs: Any) -> None:
+        """
+        Reader for DIA-NN ``report.parquet`` file.
+
+        Parameters
+        ----------
+        filename : str or Path
+            Path to PSM file.
+        *args
+            Additional positional arguments passed to the base class.
+        **kwargs
+            Additional keyword arguments passed to the base class.
+
+        """
+        super().__init__(filename, *args, **kwargs)
+
+    def __iter__(self) -> Iterator[PSM]:
+        """Iterate over file and return PSMs one-by-one."""
+        with pq.ParquetFile(self.filename) as pq_file:
+            for batch in pq_file.iter_batches():
+                for row in batch.to_pylist():
+                    yield self._get_peptide_spectrum_match(row, self.filename)
+
+    @staticmethod
+    def _get_peptide_spectrum_match(
+        psm_dict: dict[str, Any], filename: str | Path | None = None
+    ) -> PSM:
+        """Parse a single PSM from a DIA-NN ``report.parquet`` file."""
+        rescoring_features: dict[str, Any] = {}
+        for ft in RESCORING_FEATURES:
+            try:
+                rescoring_features[ft] = psm_dict[ft]
+            except KeyError:
+                continue
+
+        return PSM(
+            peptidoform=DIANNTSVReader._parse_peptidoform(
+                psm_dict["Modified.Sequence"], str(psm_dict["Precursor.Charge"])
+            ),
+            spectrum_id=psm_dict["Precursor.Id"],
+            run=psm_dict["Run"],
+            is_decoy=bool(psm_dict["Decoy"]),
+            qvalue=psm_dict["Q.Value"],
+            pep=psm_dict["PEP"],
+            score=None,  # Not returned by DIA-NN in the `report.parquet` main report :(
+            precursor_mz=psm_dict["Precursor.Mz"],
+            retention_time=psm_dict["RT"],
+            ion_mobility=psm_dict["IM"],
+            protein_list=psm_dict["Protein.Ids"].split(";"),
+            source="diann",
+            rank=None,
+            provenance_data=({"diann_filename": str(filename)} if filename else {}),
+            rescoring_features=rescoring_features,
+            metadata={},
+        )
+
+    @classmethod
+    def from_dataframe(cls, dataframe: pd.DataFrame) -> PSMList:
+        """Create a PSMList from a DIA-NN ``report.parquet`` Pandas DataFrame."""
+        records = cast(list[dict[str, Any]], dataframe.to_dict(orient="records"))
+        return PSMList(psm_list=[cls._get_peptide_spectrum_match(entry) for entry in records])

tests/test_io/test_diann.py

@@ -1,6 +1,6 @@
 """Tests for psm_utils.io.diann."""
 
-from psm_utils.io.diann import DIANNTSVReader
+from psm_utils.io.diann import DIANNParquetReader, DIANNTSVReader
 from psm_utils.psm import PSM
 
 test_psm = PSM(
@@ -52,3 +52,43 @@ def test__parse_peptidoform(self):
         reader = DIANNTSVReader("./tests/test_data/test_diann.tsv")
         for (peptide, charge), expected in test_cases:
             assert reader._parse_peptidoform(peptide, charge) == expected
+
+
+test_parquet_psm = PSM(
+    peptidoform="[UNIMOD:1]-AAAAEINVKDPKEDLETSVVDEGR/4",
+    spectrum_id="(UniMod:1)AAAAEINVKDPKEDLETSVVDEGR4",
+    run="LFQ_Orbitrap_AIF_Yeast_03",
+    collection=None,
+    spectrum=None,
+    is_decoy=False,
+    score=None,
+    qvalue=0.000548193,
+    pep=0.0104343,
+    precursor_mz=621.5723,
+    retention_time=75.2574,
+    ion_mobility=0.0,
+    protein_list=["P38156"],
+    rank=None,
+    source="diann",
+    metadata={},
+    rescoring_features={
+        "RT": 75.2574,
+        "Predicted.RT": 75.2713,
+        "iRT": 33.9222,
+        "Predicted.iRT": 33.8999,
+        "Ms1.Profile.Corr": 0.347567,
+        "Ms1.Area": 849940.0,
+        "IM": 0.0,
+        "iIM": 0.0,
+        "Predicted.IM": 0.0,
+        "Predicted.iIM": 0.0,
+    },
+)
+
+
+class TestDIANNParquetReader:
+    def test_iter(self):
+        with DIANNParquetReader("./tests/test_data/test_diann.parquet") as reader:
+            for psm in reader:
+                psm.provenance_data = {}
+                assert psm == test_parquet_psm