diff --git a/alphabase/constants/const_files/pg_reader.yaml b/alphabase/constants/const_files/pg_reader.yaml
index 9416c21f..072215a9 100644
--- a/alphabase/constants/const_files/pg_reader.yaml
+++ b/alphabase/constants/const_files/pg_reader.yaml
@@ -73,6 +73,23 @@ maxquant:
     "lfq": "^LFQ intensity(?!\\s[LHM]\\s).+$" # LFQ intensity-based quantification
     "ibaq": "^iBAQ(?!\\s[LHM]\\s).+$" # Intensity-Based Absolute Quantification
 
+# Based on PEAKS
+peaks_peptides:
+  reader_type: "peaks_peptides"
+  column_mapping:
+    "peptides": "Peptide"
+    "proteins": "proteins" # this column is added through preprocessing
+    "genes": "genes" # this column is added through preprocessing
+  measurement_regex:
+    "lfq": "^sample_\\d+$"  # PEAKS columns renamed from "Area Sample 1" to "sample_1" during preprocessing
+
+peaks_proteins:
+  reader_type: "peaks_proteins"
+  column_mapping:
+    "proteins": "proteins" # this column is added through preprocessing
+    "genes": "genes" # this column is added through preprocessing
+  measurement_regex:
+    "lfq": "^sample_\\d+$"  # PEAKS columns renamed from "Sample 1 Area" to "sample_1" during preprocessing
 
 # Based on Spectronaut 20.0 Run Pivot Report (Page 80/81)
 # https://biognosys.com/content/uploads/2025/06/Spectronaut-20-Manual.pdf
diff --git a/alphabase/pg_reader/__init__.py b/alphabase/pg_reader/__init__.py
index 99535176..17d8f8a5 100644
--- a/alphabase/pg_reader/__init__.py
+++ b/alphabase/pg_reader/__init__.py
@@ -5,6 +5,7 @@
 from .fragpipe_pg_reader import FragPipePGReader
 from .maxquant_pg_reader import MaxQuantPGReader
 from .mztab_pg_reader import MZTabPGReader
+from .peaks_pg_reader import PeaksPeptidesReader, PeaksPGReader
 from .pg_reader import pg_reader_provider
 from .spectronaut_reader import SpectronautPGReader
 
@@ -18,4 +19,6 @@
     "SpectronautPGReader",
     "FragPipePGReader",
     "MZTabPGReader",
+    "PeaksPGReader",
+    "PeaksPeptidesReader",
 ]
diff --git a/alphabase/pg_reader/keys.py b/alphabase/pg_reader/keys.py
index ec0581b3..ed565d5e 100644
--- a/alphabase/pg_reader/keys.py
+++ b/alphabase/pg_reader/keys.py
@@ -11,6 +11,11 @@ class PGCols(metaclass=ConstantsClass):
     PROTEINS
         Uniprot names of proteins in the respective protein group.
         Individual entries are separated by a semicolon in the unified output.
+    PEPTIDES
+        Peptide sequence without modifications. This is specified in the PG-reader
+        context since conceptually, proteins and peptides are just different levels of
+        aggregating the fundamental unit of measurement in bottom-up proteomics,
+        which are precursors.
     UNIPROT_IDS
         Uniprot IDs of all proteins in the respective protein group.
         Individual entries are separated by a semicolon in the unified output.
@@ -44,6 +49,7 @@ class PGCols(metaclass=ConstantsClass):
 
     # Minimal columns
     PROTEINS = "proteins"
+    PEPTIDES = "peptides"
     UNIPROT_IDS = "uniprot_ids"
     ENSEMBL_IDS = "ensembl_ids"
     GENES = "genes"
diff --git a/alphabase/pg_reader/peaks_pg_reader.py b/alphabase/pg_reader/peaks_pg_reader.py
new file mode 100644
index 00000000..3c0bcb28
--- /dev/null
+++ b/alphabase/pg_reader/peaks_pg_reader.py
@@ -0,0 +1,234 @@
+"""PEAKS protein group and peptided wide table reader."""
+
+from typing import Any, Literal, Optional, Union
+
+import pandas as pd
+
+from .keys import PGCols
+from .pg_reader import PGReaderBase, pg_reader_provider
+
+PROTEIN_GENE_SEPARATOR = "|"
+ACCESSION_COLUMN = "Accession"
+EXPECTED_PAIR_LENGTH = 2
+
+
+def _assemble_pg_gene_groups(
+    accession: str,
+    id_separator: str = PROTEIN_GENE_SEPARATOR,
+    group_separator: str = ":",
+) -> tuple[str, str]:
+    """Assemble protein and gene groups from PEAKS accession string.
+
+    Parameters
+    ----------
+    accession
+        Accession string containing protein|gene pairs separated by colons.
+        Format: "protein1|gene1:protein2|gene2:protein3|gene3"
+    id_separator
+        Character separating protein from gene within each pair (default "|").
+    group_separator
+        Character separating multiple protein|gene pairs (default ":").
+
+    Returns
+    -------
+    tuple[str, str]
+        Tuple containing (protein_group, gene_group) as semicolon-separated strings.
+
+    Example
+    -------
+        >>> accession = "P1|G1:P2|G2:P3|G3"
+        >>> _assemble_pg_gene_groups(accession)
+        ("P1;P2;P3", "G1;G2;G3")
+
+    """
+    pg_gene_list = [
+        pair.split(id_separator) for pair in accession.split(group_separator)
+    ]
+
+    proteins = []
+    genes = []
+
+    for pair in pg_gene_list:
+        if len(pair) >= EXPECTED_PAIR_LENGTH:
+            proteins.append(pair[0])
+            genes.append(pair[1])
+        elif len(pair) == 1:
+            # If no gene provided, just add the protein
+            proteins.append(pair[0])
+
+    return ";".join(proteins), ";".join(genes)
+
+
+def _split_peaks_identifiers(df: pd.DataFrame) -> pd.DataFrame:
+    """Split PEAKS protein group identifiers into separate protein and gene columns.
+
+    The 'Accession' column contains both the protein and gene identifiers separated by
+    a pipe character. There may be multiple protein|gene pairs separated by a colon (??).
+    This function assembles all proteins into one protein group and all genes into a gene
+    group, separated by semicolons.
+
+    Parameters
+    ----------
+    df
+        DataFrame containing PEAKS protein group report.
+
+    Returns
+    -------
+    pd.DataFrame
+        Modified copy of the input DataFrame with separate 'protein' and 'gene' columns.
+
+    """
+    df_copy = df.copy()
+
+    protein_groups = []
+    gene_groups = []
+
+    for accession in df_copy[ACCESSION_COLUMN]:
+        protein_group, gene_group = _assemble_pg_gene_groups(accession)
+        protein_groups.append(protein_group)
+        gene_groups.append(gene_group)
+
+    df_copy[PGCols.PROTEINS] = protein_groups
+    df_copy[PGCols.GENES] = gene_groups
+
+    return df_copy
+
+
+def _reformat_observation_indices(
+    df: pd.DataFrame,
+    modality: Literal["peptide", "protein"],
+) -> pd.DataFrame:
+    """Parse PEAKS sample column names to standardized format.
+
+    The peptide table contains sample names like Area Sample 1, Area Sample 2, etc.
+    The protein table contains sample names like Sample 1 Area, Sample 2 Area, etc.
+
+    We parse both to appropriate sample names like sample_1, sample_2, etc.
+
+    Parameters
+    ----------
+    df
+        DataFrame with PEAKS sample columns.
+    modality
+        Type of PEAKS table ("peptide" or "protein") to determine parsing strategy.
+
+    Returns
+    -------
+    pd.DataFrame
+        DataFrame with standardized column names.
+
+    """
+    if modality == "peptide":
+        # Only rename columns that match "Area Sample X" pattern
+        def parser(col_name: str) -> str:
+            if col_name.startswith("Area Sample"):
+                return col_name.lower().replace("area ", "").replace(" ", "_")
+            return col_name
+    elif modality == "protein":
+        # Only rename columns that match "Sample X Area" pattern
+        def parser(col_name: str) -> str:
+            if col_name.startswith("Sample") and col_name.endswith("Area"):
+                return col_name.lower().replace(" area", "").replace(" ", "_")
+            return col_name
+    else:
+        raise ValueError(f"Unknown modality: {modality}")
+
+    return df.rename(columns=parser)
+
+
+class PeaksPGReader(PGReaderBase):
+    """Reader for protein group matrices created by PEAKS."""
+
+    _reader_type = "peaks_proteins"
+
+    def __init__(
+        self,
+        *,
+        column_mapping: Optional[dict[str, Any]] = None,
+        measurement_regex: Union[str, Literal["lfq"], None] = "lfq",  # noqa: PYI051 lfq is a special case and not equivalent to string
+    ):
+        """Initialize PEAKS protein group matrix reader.
+
+        Parameters
+        ----------
+        column_mapping
+            Dictionary mapping alphabase column names (keys) to PEAKS column names (values).
+            If `None`, uses default mapping from configuration file.
+        measurement_regex
+            Pattern to select quantity columns
+
+                - "lfq": LFQ-corrected intensities (_LFQ suffix)
+
+            See class documentation for usage examples and `get_preconfigured_regex()` for available patterns.
+
+        """
+        super().__init__(
+            column_mapping=column_mapping, measurement_regex=measurement_regex
+        )
+
+    def _pre_process(self, df: pd.DataFrame) -> pd.DataFrame:
+        """Preprocess PEAKS protein group report and return modified copy of the dataframe.
+
+        The 'Accession' column contains both the protein and gene identifiers separated by
+        a pipe character. This method splits these identifiers into a 'protein' and a 'gene' column.
+
+        Additionally, parse the sample names to a better format.
+
+        """
+        df_processed = _split_peaks_identifiers(df)
+        return _reformat_observation_indices(
+            df_processed,
+            modality="protein",
+        )
+
+
+pg_reader_provider.register_reader("peaks_proteins", reader_class=PeaksPGReader)
+
+
+class PeaksPeptidesReader(PGReaderBase):
+    """Reader for peptide matrices created by PEAKS."""
+
+    _reader_type = "peaks_peptides"
+
+    def __init__(
+        self,
+        *,
+        column_mapping: Optional[dict[str, Any]] = None,
+        measurement_regex: Union[str, Literal["lfq"], None] = "lfq",  # noqa: PYI051 lfq is a special case and not equivalent to string
+    ):
+        """Initialize PEAKS peptide matrix reader.
+
+        Parameters
+        ----------
+        column_mapping
+            Dictionary mapping alphabase column names (keys) to PEAKS column names (values).
+            If `None`, uses default mapping from configuration file.
+        measurement_regex
+            Pattern to select quantity columns
+
+                - "lfq": LFQ-corrected intensities (_LFQ suffix)
+
+            See class documentation for usage examples and `get_preconfigured_regex()` for available patterns.
+
+        """
+        super().__init__(
+            column_mapping=column_mapping, measurement_regex=measurement_regex
+        )
+
+    def _pre_process(self, df: pd.DataFrame) -> pd.DataFrame:
+        """Preprocess PEAKS peptide report and return modified copy of the dataframe.
+
+        The 'Accession' column contains both the protein and gene identifiers separated by
+        a pipe character. This method splits these identifiers into a 'protein' and a 'gene' column.
+
+        Additionally, parse the sample names to a better format.
+
+        """
+        df_processed = _split_peaks_identifiers(df)
+        return _reformat_observation_indices(
+            df_processed,
+            modality="peptide",
+        )
+
+
+pg_reader_provider.register_reader("peaks_peptides", reader_class=PeaksPeptidesReader)
diff --git a/tests/integration/conftest.py b/tests/integration/conftest.py
index 03c4243e..8ac3fdcc 100644
--- a/tests/integration/conftest.py
+++ b/tests/integration/conftest.py
@@ -274,3 +274,44 @@ def example_directlfq_minimal(tmp_path) -> Path:
     reference = get_local_reference_data(test_case_name=TEST_FILE_NAME)
 
     return file_path, reference
+
+
+@pytest.fixture(scope="function")
+def example_peaks_proteins_csv(tmp_path) -> tuple[Path, pd.DataFrame]:
+    """Get and parse PEAKS protein group report for local testing."""
+    TEST_FILE_NAME = "pg_peaks_proteins.tsv"
+    # Note: Accession format is "protein|gene" and can have multiple pairs separated by ":"
+    TEST_DATA = """Accession,Gene,Sample 1 Area,Sample 2 Area,Sample 3 Area,Sample 4 Area
+P12345|GENE1,GENE1,1000000.5,1200000.3,1100000.7,1050000.2
+Q67890|GENE2,GENE2,500000.1,520000.9,510000.4,505000.8
+P11111|GENE3:Q22222|GENE4,GENE3,2000000.0,2100000.5,2050000.2,2020000.1
+R33333|GENE5:S44444|GENE6:T55555|GENE7,GENE5,750000.3,780000.1,760000.9,770000.5
+P99999|GENE8,GENE8,300000.0,0.0,310000.5,305000.2
+    """
+    file_path = write_test_data(
+        data=TEST_DATA, directory=tmp_path, test_case_name=TEST_FILE_NAME
+    )
+    reference = get_local_reference_data(test_case_name=TEST_FILE_NAME)
+
+    return file_path, reference
+
+
+@pytest.fixture(scope="function")
+def example_peaks_peptides_csv(tmp_path) -> tuple[Path, pd.DataFrame]:
+    """Get and parse PEAKS peptide report for local testing."""
+    TEST_FILE_NAME = "pg_peaks_peptides.tsv"
+    # Note: Accession format is "protein|gene" and can have multiple pairs separated by ":"
+    # Column naming differs from protein table: "Area Sample 1" not "Sample 1 Area"
+    TEST_DATA = """Accession,Peptide,Area Sample 1,Area Sample 2,Area Sample 3,Area Sample 4
+P12345|GENE1,PEPTIDEAAA,50000.5,52000.3,51000.7,50500.2
+Q67890|GENE2,PEPTIDEBBB,25000.1,26000.9,25500.4,25250.8
+P11111|GENE3:Q22222|GENE4,PEPTIDECCC,100000.0,105000.5,102500.2,101000.1
+R33333|GENE5:S44444|GENE6:T55555|GENE7,PEPTIDEDDD,37500.3,39000.1,38000.9,38500.5
+P99999|GENE8,PEPTIDEEEE,15000.0,0.0,15500.5,15250.2
+    """
+    file_path = write_test_data(
+        data=TEST_DATA, directory=tmp_path, test_case_name=TEST_FILE_NAME
+    )
+    reference = get_local_reference_data(test_case_name=TEST_FILE_NAME)
+
+    return file_path, reference
diff --git a/tests/integration/test_pg_reader_provider.py b/tests/integration/test_pg_reader_provider.py
index 5d5d1f7a..16d674b3 100644
--- a/tests/integration/test_pg_reader_provider.py
+++ b/tests/integration/test_pg_reader_provider.py
@@ -7,6 +7,8 @@
     FragPipePGReader,
     MaxQuantPGReader,
     MZTabPGReader,
+    PeaksPeptidesReader,
+    PeaksPGReader,
     SpectronautPGReader,
     pg_reader_provider,
 )
@@ -66,3 +68,17 @@ def test_reader_provider(self) -> None:
         reader = pg_reader_provider.get_reader("mztab")
 
         assert isinstance(reader, MZTabPGReader)
+
+
+class TestPeaksPGReaderProvider:
+    def test_reader_provider(self) -> None:
+        """Test whether reader provider initializes PEAKS protein group reader correctly."""
+        reader = pg_reader_provider.get_reader("peaks_proteins")
+
+        assert isinstance(reader, PeaksPGReader)
+
+    def test_peptides_reader_provider(self) -> None:
+        """Test whether reader provider initializes PEAKS peptides reader correctly."""
+        reader = pg_reader_provider.get_reader("peaks_peptides")
+
+        assert isinstance(reader, PeaksPeptidesReader)
diff --git a/tests/integration/test_pg_readers.py b/tests/integration/test_pg_readers.py
index 4863616a..d2f3e37d 100644
--- a/tests/integration/test_pg_readers.py
+++ b/tests/integration/test_pg_readers.py
@@ -11,6 +11,8 @@
     FragPipePGReader,
     MaxQuantPGReader,
     MZTabPGReader,
+    PeaksPeptidesReader,
+    PeaksPGReader,
     SpectronautPGReader,
 )
 from alphabase.pg_reader.keys import PGCols
@@ -248,3 +250,131 @@ def test_import_minimal_example(self, example_directlfq_minimal: str) -> None:
         result_df = reader.import_file(file_path=file_path)
 
         pd.testing.assert_frame_equal(result_df, reference)
+
+
+class TestPeaksPGReader:
+    """Test PEAKS protein group reader"""
+
+    def test_import_peaks_proteins(
+        self, example_peaks_proteins_csv: tuple[str, pd.DataFrame]
+    ) -> None:
+        """Test import of PEAKS protein group file"""
+        file_path, reference = example_peaks_proteins_csv
+
+        reader = PeaksPGReader()
+
+        result_df = reader.import_file(file_path=file_path)
+
+        pd.testing.assert_frame_equal(result_df, reference)
+
+    def test_protein_gene_splitting(
+        self, example_peaks_proteins_csv: tuple[str, pd.DataFrame]
+    ) -> None:
+        """Test that protein|gene pairs are correctly split and grouped"""
+        file_path, _ = example_peaks_proteins_csv
+
+        reader = PeaksPGReader()
+        result_df = reader.import_file(file_path=file_path)
+
+        # Check that index has correct columns
+        assert result_df.index.names == [PGCols.PROTEINS, PGCols.GENES]
+
+        # Check shape: 5 proteins x 4 samples
+        assert result_df.shape == (5, 4)
+
+        # Check that multi-protein groups are correctly assembled
+        assert "P11111;Q22222" in result_df.index.get_level_values(PGCols.PROTEINS)
+        assert "GENE3;GENE4" in result_df.index.get_level_values(PGCols.GENES)
+
+        # Check triple protein group
+        assert "R33333;S44444;T55555" in result_df.index.get_level_values(
+            PGCols.PROTEINS
+        )
+        assert "GENE5;GENE6;GENE7" in result_df.index.get_level_values(PGCols.GENES)
+
+    def test_column_renaming(
+        self, example_peaks_proteins_csv: tuple[str, pd.DataFrame]
+    ) -> None:
+        """Test that column names are standardized from PEAKS format"""
+        file_path, _ = example_peaks_proteins_csv
+
+        reader = PeaksPGReader()
+        result_df = reader.import_file(file_path=file_path)
+
+        # Check standardized column names
+        assert "sample_1" in result_df.columns
+        assert "sample_2" in result_df.columns
+        assert "sample_3" in result_df.columns
+        assert "sample_4" in result_df.columns
+
+        # Ensure original names are gone
+        assert "Sample 1 Area" not in result_df.columns
+        assert "Sample 2 Area" not in result_df.columns
+
+
+class TestPeaksPeptidesReader:
+    """Test PEAKS peptide reader"""
+
+    def test_import_peaks_peptides(
+        self, example_peaks_peptides_csv: tuple[str, pd.DataFrame]
+    ) -> None:
+        """Test import of PEAKS peptide file"""
+        file_path, reference = example_peaks_peptides_csv
+
+        reader = PeaksPeptidesReader()
+
+        result_df = reader.import_file(file_path=file_path)
+
+        pd.testing.assert_frame_equal(result_df, reference)
+
+    def test_peptide_protein_gene_splitting(
+        self, example_peaks_peptides_csv: tuple[str, pd.DataFrame]
+    ) -> None:
+        """Test that protein|gene pairs are correctly split and grouped in peptide data"""
+        file_path, _ = example_peaks_peptides_csv
+
+        reader = PeaksPeptidesReader()
+        result_df = reader.import_file(file_path=file_path)
+
+        # Check that index has correct columns (peptides first per YAML config)
+        assert result_df.index.names == [
+            PGCols.PEPTIDES,
+            PGCols.PROTEINS,
+            PGCols.GENES,
+        ]
+
+        # Check shape: 5 peptides x 4 samples
+        assert result_df.shape == (5, 4)
+
+        # Check that multi-protein groups are correctly assembled
+        assert "P11111;Q22222" in result_df.index.get_level_values(PGCols.PROTEINS)
+        assert "GENE3;GENE4" in result_df.index.get_level_values(PGCols.GENES)
+
+        # Check peptide sequences are present
+        assert "PEPTIDEAAA" in result_df.index.get_level_values(PGCols.PEPTIDES)
+        assert "PEPTIDECCC" in result_df.index.get_level_values(PGCols.PEPTIDES)
+
+        # Check triple protein group
+        assert "R33333;S44444;T55555" in result_df.index.get_level_values(
+            PGCols.PROTEINS
+        )
+        assert "GENE5;GENE6;GENE7" in result_df.index.get_level_values(PGCols.GENES)
+
+    def test_column_renaming(
+        self, example_peaks_peptides_csv: tuple[str, pd.DataFrame]
+    ) -> None:
+        """Test that column names are standardized from PEAKS peptide format"""
+        file_path, _ = example_peaks_peptides_csv
+
+        reader = PeaksPeptidesReader()
+        result_df = reader.import_file(file_path=file_path)
+
+        # Check standardized column names
+        assert "sample_1" in result_df.columns
+        assert "sample_2" in result_df.columns
+        assert "sample_3" in result_df.columns
+        assert "sample_4" in result_df.columns
+
+        # Ensure original names are gone
+        assert "Area Sample 1" not in result_df.columns
+        assert "Area Sample 2" not in result_df.columns