Moved raw data files to separate directory

CF-MS_Homo_sapiens_PPI.py

@@ -1,290 +0,0 @@
-from __future__ import annotations
-import os
-from typing import Dict, Iterable, List, Tuple
-import datasets
-
-
-
-logger = datasets.logging.get_logger(__name__)
-
-_DESCRIPTION = """
-Co-fractionation mass spectrometry (CF-MS) elution traces and PPI labels.
-
-- .elut files: rows = proteins (UniProt IDs), columns = fractions (PSM counts).
-- .txt files: tab-separated UniProt ID pairs. Use separate files for positives and negatives
-"""
-
-_HUB_BASE = "hf://datasets/viridono/CF-MS_Homo_sapiens_PPI/"
-
-# --------------------------------------------------------------------
-# Defaults: your file names (searched under base_dir if data_files unset)
-# --------------------------------------------------------------------
-DEFAULT_ELUT_FILES = [
-    "CB660_neural_stem_cell_IEX_Wan_2015.elut",
-    "G166_glioma_stem_cell_IEX_Wan_2015_Hs_HCW_2.elut",
-    "G166_glioma_stem_cell_IEX_Wan_2015_Hs_HCW_3.elut",
-    "IEX_Wan_2015_Hs_IEX_1.elut",
-    "IEX_Wan_2015_Hs_IEX_2.elut",
-    "IEX_Wan_2015_Hs_HCW_4.elut",
-    "IEX_Wan_2015_Hs_HCW_5.elut",
-    "IEX_Wan_2015_Hs_HCW_6.elut",
-    "IEX_Wan_2015_Hs_HCW_7.elut",
-    "IEX_Wan_2015_Hs_HCW_8.elut",
-    "IEX_Wan_2015_Hs_HCW_9.elut",
-    "HEK_293_T_cells_SEC_Mallam_2019_C1.elut",
-    "HEK_293_T_cells_SEC_Mallam_2019_C2.elut",
-    "NTera2_embryonal_carcinoma_stem_cells_IEX_Moutaoufik_2019_2_R1.elut",
-    "NTera2_embryonal_carcinoma_stem_cells_IEX_Moutaoufik_2019_2_R2.elut",
-    "NTera2_embryonal_carcinoma_stem_cells_IEX_Moutaoufik_2019_R1.elut",
-    "NTera2_embryonal_carcinoma_stem_cells_IEX_Moutaoufik_2019_R2.elut",
-    "NTera2_embryonal_carcinoma_stem_cells_SEC_Moutaoufik_2019_2_R1.elut",
-    "NTera2_embryonal_carcinoma_stem_cells_SEC_Moutaoufik_2019_2_R2.elut",
-    "NTera2_embryonal_carcinoma_stem_cells_SEC_Moutaoufik_2019_R1.elut",
-    "NTera2_embryonal_carcinoma_stem_cells_SEC_Moutaoufik_2019_R2.elut",
-    "T98G_glioblastoma_multiforme_cells_SEC_Conelly_2018_Bio1.elut",
-    "T98G_glioblastoma_multiforme_cells_SEC_Conelly_2018_Bio2.elut",
-    "U2OS_cells_SEC_Kirkwood_2013_rep1.elut",
-    "U2OS_cells_SEC_Kirkwood_2013_rep2.elut",
-    "U2OS_cells_SEC_Kirkwood_2013_rep3.elut",
-    "U2OS_cells_SEC_Larance_2016_PT3281S1.elut",
-    "U2OS_cells_SEC_Larance_2016_PT3441S1.elut",
-    "U2OS_cells_SEC_Larance_2016_PT3442S1.elut",
-    "U2OS_cells_SEC_Larance_2016_PT3701S1.elut",
-    "U2OS_cells_SEC_Larance_2016_PTSS3801.elut",
-    "U2OS_cells_SEC_Larance_2016_PTSS3802.elut",
-]
-
-
-DEFAULT_PAIR_FILES = {
-    # split -> (pos, neg)
-    "train": (
-        "intact_complex_merge_20230309.train_ppis.txt",
-        "intact_complex_merge_20230309.neg_train_ppis.txt",
-    ),
-    "test": (
-        "intact_complex_merge_20230309.test_ppis.txt",
-        "intact_complex_merge_20230309.neg_test_ppis.txt",
-    ),
-}
-
-
-class cfmsConfig(datasets.BuilderConfig):
-    """ BuilderConfig for CFMS dataset"""
-
-    def __init__(self, view: str = "proteins", **kwargs):
-        super().__init__(**kwargs)
-        self.view = view
-
-
-class cfmsElution(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("0.1.0")
-    DEFAULT_CONFIG_NAME = "pairs" # Make 'pairs' the default
-
-    # Two "views" (configurations) of dataset: proteins or protein pairs
-    BUILDER_CONFIGS = [
-            cfmsConfig(
-                name="proteins",
-                view="proteins",
-                version=VERSION,
-                description="Individual protein elution traces per CF-MS experiment."
-            ),
-            cfmsConfig(
-                name="pairs",
-                view="pairs",
-                version=VERSION,
-                description="Pairwise protein elution traces from same CF-MS experiment with labels denoting whether they interact."
-            ),
-    ]
-
-    # Metadata for different configurations of dataset
-    def _info(self):
-        if self.config.view == "proteins":
-            features = datasets.Features(
-                {
-                    "experiment_id": datasets.Value("string"),
-                    "uniprot_id": datasets.Value("string"),
-                    "fraction_names": datasets.Sequence(datasets.Value("string")),
-                    "trace": datasets.Sequence(datasets.Value("int32")),
-                }
-            )
-        else:
-            features = features=datasets.Features(
-                {
-                    "experiment_id": datasets.Value("string"),
-                    "uniprot_id1": datasets.Value("string"),
-                    "uniprot_id2": datasets.Value("string"),
-                    "elut_trace1": datasets.Sequence(datasets.Value("int32")),
-                    "elut_trace2": datasets.Sequence(datasets.Value("int32")),
-                    "label": datasets.ClassLabel(names=["neg", "pos"]),
-                }
-            )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-        )
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager):
-        data_files = dict(self.config.data_files or {})
-
-        # "proteins" view
-        if self.config.view == "proteins":
-            urls = _ensure_list(data_files.get("elut", DEFAULT_ELUT_FILES))
-            paths = dl_manager.download(urls)
-            return [datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"elut_files": _as_iter(paths)}
-            )]
-
-        # "pairs" view
-        else:
-            split_specs = []
-            for split_name in ["train", "test"]:
-                pos_key = f"{split_name}_pos"
-                neg_key = f"{split_name}_neg"
-
-                pos, neg = DEFAULT_PAIR_FILES[split_name]
-                pos_urls, neg_urls = [pos], [neg]
-
-                elut_urls = _ensure_list(data_files.get("elut", DEFAULT_ELUT_FILES))
-
-                pos_paths = dl_manager.download(pos_urls)
-                neg_paths = dl_manager.download(neg_urls)
-                elut_paths = dl_manager.download(elut_urls)
-
-                split_specs.append(
-                    datasets.SplitGenerator(
-                        name=getattr(datasets.Split, split_name.upper()),
-                        gen_kwargs={
-                            "split_name": split_name,
-                            "pos_files": _as_iter(pos_paths),
-                            "neg_files": _as_iter(neg_paths),
-                            "elut_files": _as_iter(elut_paths),
-                        },
-                    )
-                )
-
-            return split_specs
-                
-
-
-    def _generate_examples(self, **kwargs):
-        if self.config.view == "proteins":
-            for elut_path in _as_iter(kwargs["elut_files"]):
-                yield from self._yield_protein_examples(elut_path)
-            return
-
-        pos_files = list(_as_iter(kwargs.get("pos_files")))
-        neg_files = list(_as_iter(kwargs.get("neg_files")))
-        elut_files = list(_as_iter(kwargs.get("elut_files")))
-        split_name = kwargs.get("split_name", "unsplit")
-
-        elut_tables: Dict[str, Tuple[List[str], Dict[str, List[int]]]] = {}
-        for elut_path in elut_files:
-            try:
-                exp_id, frac_names, table = _read_elut_table(elut_path)
-                elut_tables[exp_id] = (frac_names, table)
-            except Exception as e:
-                logger.warning("Failed to read %s: %s", elut_path, e)
-
-        def _emit_for_pair(a: str, b: str, label: str) -> Iterator[Tuple[str, dict]]:
-            for exp_id, (_fracs, table) in elut_tables.items():
-                ta = table.get(a)
-                tb = table.get(b)
-                if ta is None or tb is None:
-                    continue
-                key = f"{split_name}::{exp_id}::{a}::{b}"
-                yield key, {
-                    "experiment_id": exp_id,
-                    "uniprot_id1": a,
-                    "uniprot_id2": b,
-                    "elut_trace1": ta,
-                    "elut_trace2": tb,
-                    "label": label,
-                }
-
-        for path in pos_files:
-            for a, b in _read_pair_file(path):
-                for ex in _emit_for_pair(a, b, "pos"):
-                    yield ex
-
-        for path in neg_files:
-            for a, b in _read_pair_file(path):
-                for ex in _emit_for_pair(a, b, "neg"):
-                    yield ex
-
-
-    # --- HELPER FUNCTIONS ---
-    def _yield_protein_examples(self, elut_path: str):
-        exp_id, fraction_names, table = _read_elut_table(elut_path)
-        for i, (uniprot_id, trace) in enumerate(table.items()):
-            key = f"{exp_id}::{uniprot_id}::{i}"
-            yield key, {
-                "experiment_id": exp_id,
-                "uniprot_id": uniprot_id,
-                "fraction_names": fraction_names,
-                "trace": trace,
-            }
-
-
-
-
-
-def _read_elut_table(path: str) -> Tuple[str, List[str], Dict[str, List[int]]]:
-    experiment_id = os.path.splitext(os.path.basename(path))[0]
-    table: Dict[str, List[int]] = {}
-
-    with open(path, "r", encoding="utf-8", errors="ignore") as f:
-        first = f.readline().rstrip("\n\r")
-        if not first:
-            return experiment_id, [], {}
-        cols = first.split("\t")
-
-        first_cell = cols[0].strip().lower() if cols else ""
-        if first_cell in {"uniprot", "uniprot_id", "protein", ""}:
-            fraction_names = cols[1:]
-        else:
-            fraction_names = cols[1:]
-
-        for line in f:
-            line = line.rstrip("\n\r")
-            if not line:
-                continue
-            toks = line.split("\t")
-            if not toks:
-                continue
-            uniprot_id = toks[0]
-            # Remaining fields are counts per fraction; blanks -> 0
-            trace: Li8st[int] = []
-            for x in toks[1:]:
-                if x == "" or x is None:
-                    trace.append(0)
-                else:
-                    try:
-                        trace.append(int(float(x)))
-                    except ValueError:
-                        trace.append(0)
-            table[uniprot_id] = trace
-
-    return experiment_id, fraction_names, table
-
-
-def _read_pair_file(path: str) -> Iterable[Tuple[str, str]]:
-    with open(path, "r", encoding="utf-8", errors="ignore") as f:
-        for line in f:
-            line = line.strip()
-            if not line or line.startswith("#"):
-                continue
-            parts = line.split()
-            if len(parts) != 2:
-                continue
-            yield parts[0], parts[1]
-
-
-def _ensure_list(x):
-    if x is None:
-        return []
-    return x if isinstance(x, list) else [x]
-
-
-def _as_iter(x):
-    return x if isinstance(x, (list, tuple)) else ([x] if x else [])