diff --git a/tests/unit/test_helpers.py b/tests/unit/test_helpers.py
deleted file mode 100644
index 2bdd459..0000000
--- a/tests/unit/test_helpers.py
+++ /dev/null
@@ -1,221 +0,0 @@
-import pytest
-import pytest_mock
-from pathlib import Path
-
-
-import numpy as np
-from Bio import AlignIO
-from Bio import SeqIO
-from Bio.Seq import Seq
-from Bio.SeqRecord import SeqRecord
-from Bio.Align import MultipleSeqAlignment
-
-from clipkit.helpers import (
-    count_characters_at_position,
-    get_gap_chars,
-    report_column_features,
-    determine_site_classification_type,
-    create_msa,
-    write_trim_msa,
-    write_keep_msa,
-    SeqType,
-)
-from clipkit.files import FileFormat
-from clipkit.modes import SiteClassificationType, TrimmingMode, trim, should_keep_site
-from clipkit.settings import DEFAULT_AA_GAP_CHARS, DEFAULT_NT_GAP_CHARS
-
-
-here = Path(__file__)
-
-
-@pytest.fixture
-def sample_msa():
-    return MultipleSeqAlignment(
-        [
-            SeqRecord(
-                seq=Seq("['A']"),
-                id="1",
-                name="<unknown name>",
-                description="",
-                dbxrefs=[],
-            ),
-            SeqRecord(
-                seq=Seq("['A']"),
-                id="2",
-                name="<unknown name>",
-                description="",
-                dbxrefs=[],
-            ),
-            SeqRecord(
-                seq=Seq("['A']"),
-                id="3",
-                name="<unknown name>",
-                description="",
-                dbxrefs=[],
-            ),
-            SeqRecord(
-                seq=Seq("['A']"),
-                id="4",
-                name="<unknown name>",
-                description="",
-                dbxrefs=[],
-            ),
-            SeqRecord(
-                seq=Seq("['A']"),
-                id="5",
-                name="<unknown name>",
-                description="",
-                dbxrefs=[],
-            ),
-        ]
-    )
-
-
-class TestCountCharactersAtPosition(object):
-    def test_gives_count_for_each_char(self):
-        ## setup
-        s = "ACTTTGGG"
-
-        ## execution
-        res = count_characters_at_position(s, DEFAULT_NT_GAP_CHARS)
-
-        ## check results
-        # test that each character has an associated key
-        for char in s:
-            assert char in res.keys()
-
-        # test that the len of the res is equal to the
-        # number of unique string characters
-        assert len(res) == len(set(s))
-
-
-class TestGetSequenceAtPositionAndReportFeatures(object):
-    def test_gets_sequence_and_gappyness(self):
-        ## setup
-        alignment = AlignIO.read(f"{here.parent}/examples/simple.fa", "fasta")
-        i = 5
-
-        ## execution
-        seq, gappyness = report_column_features(alignment, i, DEFAULT_AA_GAP_CHARS)
-
-        ## check results
-        # test output types
-        assert isinstance(seq, str)
-        assert isinstance(gappyness, float)
-
-
-class TestParsimonyInformativeOrConstant(object):
-    def test_determine_site_classification_type(self):
-        ## set up
-        num_occurences_pi = {"A": 5, "T": 10, "G": 2, "C": 4}
-        num_occurences_const = {"T": 10}
-        num_occurences_singleton = {"A": 1, "T": 2}
-        num_occurences_other = {"A": 1}
-
-        ## execution
-        res_num_occurences_pi = determine_site_classification_type(num_occurences_pi)
-        res_num_occurences_const = determine_site_classification_type(
-            num_occurences_const
-        )
-        res_num_occurences_singleton = determine_site_classification_type(
-            num_occurences_singleton
-        )
-        res_num_occurences_other = determine_site_classification_type(
-            num_occurences_other
-        )
-
-        ## check results
-        assert res_num_occurences_pi is SiteClassificationType.parsimony_informative
-        assert res_num_occurences_const is SiteClassificationType.constant
-        assert res_num_occurences_singleton is SiteClassificationType.singleton
-        assert res_num_occurences_other is SiteClassificationType.other
-
-
-class TestPopulateEmptyKeepDAndTrimD(object):
-    def test_create_msa(self):
-        ## set up
-        alignment = AlignIO.read(f"{here.parent}/examples/simple.fa", "fasta")
-
-        ## execution
-        keep_msa, trim_msa = create_msa(alignment, True)
-
-        ## check results
-        expected_keep_data = {
-            "1": np.array([b"", b"", b"", b"", b"", b""]),
-            "2": np.array([b"", b"", b"", b"", b"", b""]),
-            "3": np.array([b"", b"", b"", b"", b"", b""]),
-            "4": np.array([b"", b"", b"", b"", b"", b""]),
-            "5": np.array([b"", b"", b"", b"", b"", b""]),
-        }
-        expected_trim_data = {
-            "1": np.array([b"", b"", b"", b"", b"", b""]),
-            "2": np.array([b"", b"", b"", b"", b"", b""]),
-            "3": np.array([b"", b"", b"", b"", b"", b""]),
-            "4": np.array([b"", b"", b"", b"", b"", b""]),
-            "5": np.array([b"", b"", b"", b"", b"", b""]),
-        }
-
-        assert expected_keep_data.keys() == keep_msa._data.keys()
-        assert all(
-            np.array_equal(expected_keep_data[key], keep_msa._data[key])
-            for key in expected_keep_data
-        )
-        assert expected_trim_data.keys() == trim_msa._data.keys()
-        assert all(
-            np.array_equal(expected_trim_data[key], trim_msa._data[key])
-            for key in expected_trim_data
-        )
-
-
-class TestWriteKeepD(object):
-    def test_write_keep_msa_writes_file(self, mocker, sample_msa):
-        ## set up
-        alignment = AlignIO.read(f"{here.parent}/examples/single_site.fa", "fasta")
-        keep_msa, _ = create_msa(alignment, True)
-
-        out_file = "output_file_name.fa"
-        out_file_format = FileFormat.fasta
-        mock_msa = mocker.patch("clipkit.msa.MultipleSeqAlignment")
-        mock_msa.return_value = sample_msa
-        mock_write = mocker.patch("clipkit.helpers.SeqIO.write")
-
-        ## execution
-        write_keep_msa(keep_msa, out_file, out_file_format)
-
-        ## check results
-        mock_write.assert_called_once_with(sample_msa, out_file, out_file_format.value)
-
-
-class TestWriteTrimD(object):
-    def test_write_trim_msa_calls_seqio_write(self, mocker, sample_msa):
-        ## set up
-        alignment = AlignIO.read(f"{here.parent}/examples/single_site.fa", "fasta")
-        _, trim_msa = create_msa(alignment, True)
-
-        out_file = "output_file_name.fa"
-        out_file_format = FileFormat.fasta
-        mock_msa = mocker.patch("clipkit.msa.MultipleSeqAlignment")
-        mock_msa.return_value = sample_msa
-        mock_write = mocker.patch("clipkit.helpers.SeqIO.write")
-
-        ## execution
-        write_trim_msa(trim_msa, out_file, out_file_format)
-
-        ## check results
-        expected_completmentOut = f"{out_file}.complement"
-        mock_write.assert_called_once_with(
-            sample_msa, expected_completmentOut, out_file_format.value
-        )
-
-
-class TestGetGapChars(object):
-    def test_get_gap_chars(self):
-        ## set up
-        seq_type = SeqType.aa
-
-        ## execution
-        res_seq_type = get_gap_chars(seq_type)
-
-        ## check results
-        expected_res = DEFAULT_AA_GAP_CHARS
-        assert expected_res == res_seq_type
diff --git a/tests/unit/test_modes.py b/tests/unit/test_modes.py
deleted file mode 100644
index 11fb474..0000000
--- a/tests/unit/test_modes.py
+++ /dev/null
@@ -1,421 +0,0 @@
-import pytest
-from pathlib import Path
-
-import numpy as np
-from Bio import AlignIO
-from clipkit.modes import SiteClassificationType, TrimmingMode, trim, should_keep_site
-from clipkit.msa import MSA
-from clipkit.helpers import create_msa
-
-
-here = Path(__file__)
-
-
-class TestModes(object):
-    def test_should_keep_site_kpi_gappy_keep(self):
-        ## setup
-        mode = TrimmingMode.kpi_gappy
-        gappyness = 0.00
-        gaps = 0.9
-
-        assert (
-            should_keep_site(
-                mode, SiteClassificationType.parsimony_informative, gappyness, gaps
-            )
-            is True
-        )
-
-    def test_should_keep_site_kpi_gappy_trim(self):
-        ## setup
-        mode = TrimmingMode.kpi_gappy
-        gappyness = 0.00
-        gaps = 0.9
-
-        assert (
-            should_keep_site(mode, SiteClassificationType.constant, gappyness, gaps)
-            is False
-        )
-
-    def test_should_keep_site_gappy_keep(self):
-        ## setup
-        mode = TrimmingMode.gappy
-        site_classification_type = SiteClassificationType.parsimony_informative
-        gappyness = 0.00
-        gaps_threshold = 0.9
-
-        assert (
-            should_keep_site(mode, site_classification_type, gappyness, gaps_threshold)
-            is True
-        )
-
-    def test_should_keep_site_gappy_trim(self):
-        ## setup
-        mode = TrimmingMode.gappy
-        site_classification_type = SiteClassificationType.parsimony_informative
-        gappyness = 0.95
-        gaps_threshold = 0.9
-
-        assert (
-            should_keep_site(mode, site_classification_type, gappyness, gaps_threshold)
-            is False
-        )
-
-    def test_should_keep_site_kpi_keep(self):
-        ## setup
-        mode = TrimmingMode.kpi
-        site_classification_type = SiteClassificationType.parsimony_informative
-        gappyness = 0.00
-        gaps_threshold = 0.9
-
-        assert should_keep_site(
-            mode, site_classification_type, gappyness, gaps_threshold
-        )
-
-    def test_should_keep_site_kpi_trim(self):
-        ## setup
-        mode = TrimmingMode.kpi
-        site_classification_type = SiteClassificationType.other
-        gappyness = 0.95
-        gaps_threshold = 0.9
-
-        assert (
-            should_keep_site(mode, site_classification_type, gappyness, gaps_threshold)
-            is False
-        )
-
-    def test_should_keep_site_kpic_keep(self):
-        ## setup
-        mode = TrimmingMode.kpic
-        site_classification_type = SiteClassificationType.constant
-        gappyness = 0.95
-        gaps_threshold = 0.9
-
-        assert should_keep_site(
-            mode, site_classification_type, gappyness, gaps_threshold
-        )
-
-    def test_should_keep_site_kpic_trim(self):
-        ## setup
-        mode = TrimmingMode.kpic
-        site_classification_type = SiteClassificationType.other
-        gappyness = 0.95
-        gaps_threshold = 0.9
-
-        assert (
-            should_keep_site(mode, site_classification_type, gappyness, gaps_threshold)
-            is False
-        )
-
-    def test_should_keep_site_kpic_gappy_keep(self):
-        ## setup
-        mode = TrimmingMode.kpic_gappy
-        site_classification_type = SiteClassificationType.constant
-        gappyness = 0.2
-        gaps_threshold = 0.9
-
-        assert should_keep_site(
-            mode, site_classification_type, gappyness, gaps_threshold
-        )
-
-    def test_should_keep_site_kpic_gappy_trim(self):
-        ## setup
-        mode = TrimmingMode.kpic_gappy
-        site_classification_type = SiteClassificationType.constant
-        gappyness = 0.95
-        gaps_threshold = 0.9
-
-        assert (
-            should_keep_site(mode, site_classification_type, gappyness, gaps_threshold)
-            is False
-        )
-
-    def test_gappy_mode(self):
-        ## setup
-        gappyness = 0
-        site_classification_type = SiteClassificationType.constant
-        site_classification_counts = {
-            SiteClassificationType.parsimony_informative: 0,
-            SiteClassificationType.constant: 0,
-            SiteClassificationType.singleton: 0,
-            SiteClassificationType.other: 0,
-        }
-        i = 2
-        gaps_threshold = 0.9
-        alignment = AlignIO.read(f"{here.parent}/examples/simple.fa", "fasta")
-        use_log = False
-
-        keep_msa, trim_msa = create_msa(alignment)
-
-        ## execution
-        keep_msa, trim_msa = trim(
-            gappyness,
-            site_classification_type,
-            site_classification_counts,
-            keep_msa,
-            trim_msa,
-            i,
-            gaps_threshold,
-            alignment,
-            TrimmingMode.gappy,
-            use_log,
-        )
-
-        ## check results
-        expected_keep_data = {
-            "1": np.array([b"", b"", b"G", b"", b"", b""]),
-            "2": np.array([b"", b"", b"G", b"", b"", b""]),
-            "3": np.array([b"", b"", b"G", b"", b"", b""]),
-            "4": np.array([b"", b"", b"A", b"", b"", b""]),
-            "5": np.array([b"", b"", b"a", b"", b"", b""]),
-        }
-        expected_trim_data = {
-            "1": np.array([b"", b"", b"", b"", b"", b""]),
-            "2": np.array([b"", b"", b"", b"", b"", b""]),
-            "3": np.array([b"", b"", b"", b"", b"", b""]),
-            "4": np.array([b"", b"", b"", b"", b"", b""]),
-            "5": np.array([b"", b"", b"", b"", b"", b""]),
-        }
-
-        assert expected_keep_data.keys() == keep_msa._data.keys()
-        assert all(
-            np.array_equal(expected_keep_data[key], keep_msa._data[key])
-            for key in expected_keep_data
-        )
-        assert expected_trim_data.keys() == trim_msa._data.keys()
-        assert all(
-            np.array_equal(expected_trim_data[key], trim_msa._data[key])
-            for key in expected_trim_data
-        )
-
-    def test_kpi_gappy_mode(self):
-        ## setup
-        gappyness = 0
-        site_classification_type = SiteClassificationType.constant
-        site_classification_counts = {
-            SiteClassificationType.parsimony_informative: 0,
-            SiteClassificationType.constant: 0,
-            SiteClassificationType.singleton: 0,
-            SiteClassificationType.other: 0,
-        }
-        i = 1
-        gaps_threshold = 0.9
-        alignment = AlignIO.read(f"{here.parent}/examples/simple.fa", "fasta")
-        use_log = False
-
-        keep_msa, trim_msa = create_msa(alignment)
-
-        ## execution
-        keep_msa, trim_msa = trim(
-            gappyness,
-            site_classification_type,
-            site_classification_counts,
-            keep_msa,
-            trim_msa,
-            i,
-            gaps_threshold,
-            alignment,
-            TrimmingMode.kpi_gappy,
-            use_log,
-        )
-
-        ## check results
-        expected_keep_data = {
-            "1": np.array([b"", b"", b"", b"", b"", b""]),
-            "2": np.array([b"", b"", b"", b"", b"", b""]),
-            "3": np.array([b"", b"", b"", b"", b"", b""]),
-            "4": np.array([b"", b"", b"", b"", b"", b""]),
-            "5": np.array([b"", b"", b"", b"", b"", b""]),
-        }
-        expected_trim_data = {
-            "1": np.array([b"", b"-", b"", b"", b"", b""]),
-            "2": np.array([b"", b"-", b"", b"", b"", b""]),
-            "3": np.array([b"", b"-", b"", b"", b"", b""]),
-            "4": np.array([b"", b"G", b"", b"", b"", b""]),
-            "5": np.array([b"", b"C", b"", b"", b"", b""]),
-        }
-
-        assert expected_keep_data.keys() == keep_msa._data.keys()
-        assert all(
-            np.array_equal(expected_keep_data[key], keep_msa._data[key])
-            for key in expected_keep_data
-        )
-        assert expected_trim_data.keys() == trim_msa._data.keys()
-        assert all(
-            np.array_equal(expected_trim_data[key], trim_msa._data[key])
-            for key in expected_trim_data
-        )
-
-    def test_kpi_mode(self):
-        ## setup
-        gappyness = 0
-        site_classification_type = SiteClassificationType.parsimony_informative
-        site_classification_counts = {
-            SiteClassificationType.parsimony_informative: 0,
-            SiteClassificationType.constant: 0,
-            SiteClassificationType.singleton: 0,
-            SiteClassificationType.other: 0,
-        }
-        i = 5
-        gaps_threshold = 0.9
-        alignment = AlignIO.read(f"{here.parent}/examples/simple.fa", "fasta")
-        use_log = False
-
-        keep_msa, trim_msa = create_msa(alignment, True)
-
-        ## execution
-        keep_msa, trim_msa = trim(
-            gappyness,
-            site_classification_type,
-            site_classification_counts,
-            keep_msa,
-            trim_msa,
-            i,
-            gaps_threshold,
-            alignment,
-            TrimmingMode.kpi,
-            use_log,
-        )
-
-        ## check results
-        expected_keep_data = {
-            "1": np.array([b"", b"", b"", b"", b"", b"T"]),
-            "2": np.array([b"", b"", b"", b"", b"", b"T"]),
-            "3": np.array([b"", b"", b"", b"", b"", b"A"]),
-            "4": np.array([b"", b"", b"", b"", b"", b"A"]),
-            "5": np.array([b"", b"", b"", b"", b"", b"-"]),
-        }
-        expected_trim_data = {
-            "1": np.array([b"", b"", b"", b"", b"", b""]),
-            "2": np.array([b"", b"", b"", b"", b"", b""]),
-            "3": np.array([b"", b"", b"", b"", b"", b""]),
-            "4": np.array([b"", b"", b"", b"", b"", b""]),
-            "5": np.array([b"", b"", b"", b"", b"", b""]),
-        }
-
-        assert expected_keep_data.keys() == keep_msa._data.keys()
-        assert all(
-            np.array_equal(expected_keep_data[key], keep_msa._data[key])
-            for key in expected_keep_data
-        )
-        assert expected_trim_data.keys() == trim_msa._data.keys()
-        assert all(
-            np.array_equal(expected_trim_data[key], trim_msa._data[key])
-            for key in expected_trim_data
-        )
-
-    def test_kpic_mode(self):
-        ## setup
-        gappyness = 0
-        site_classification_type = SiteClassificationType.constant
-        site_classification_counts = {
-            SiteClassificationType.parsimony_informative: 0,
-            SiteClassificationType.constant: 0,
-            SiteClassificationType.singleton: 0,
-            SiteClassificationType.other: 0,
-        }
-        i = 0
-        gaps_threshold = 0.9
-        alignment = AlignIO.read(f"{here.parent}/examples/simple.fa", "fasta")
-        use_log = False
-
-        keep_msa, trim_msa = create_msa(alignment, True)
-
-        ## execution
-        keep_msa, trim_msa = trim(
-            gappyness,
-            site_classification_type,
-            site_classification_counts,
-            keep_msa,
-            trim_msa,
-            i,
-            gaps_threshold,
-            alignment,
-            TrimmingMode.kpic_gappy,
-            use_log,
-        )
-
-        ## check results
-        expected_keep_data = {
-            "1": np.array([b"A", b"", b"", b"", b"", b""]),
-            "2": np.array([b"A", b"", b"", b"", b"", b""]),
-            "3": np.array([b"A", b"", b"", b"", b"", b""]),
-            "4": np.array([b"A", b"", b"", b"", b"", b""]),
-            "5": np.array([b"A", b"", b"", b"", b"", b""]),
-        }
-        expected_trim_data = {
-            "1": np.array([b"", b"", b"", b"", b"", b""]),
-            "2": np.array([b"", b"", b"", b"", b"", b""]),
-            "3": np.array([b"", b"", b"", b"", b"", b""]),
-            "4": np.array([b"", b"", b"", b"", b"", b""]),
-            "5": np.array([b"", b"", b"", b"", b"", b""]),
-        }
-
-        assert expected_keep_data.keys() == keep_msa._data.keys()
-        assert all(
-            np.array_equal(expected_keep_data[key], keep_msa._data[key])
-            for key in expected_keep_data
-        )
-        assert expected_trim_data.keys() == trim_msa._data.keys()
-        assert all(
-            np.array_equal(expected_trim_data[key], trim_msa._data[key])
-            for key in expected_trim_data
-        )
-
-    def test_kpic_gappy_mode(self):
-        ## setup
-        gappyness = 0.2
-        site_classification_type = SiteClassificationType.singleton
-        site_classification_counts = {
-            SiteClassificationType.parsimony_informative: 0,
-            SiteClassificationType.constant: 0,
-            SiteClassificationType.singleton: 0,
-            SiteClassificationType.other: 0,
-        }
-
-        i = 3
-        gaps_threshold = 0.9
-        alignment = AlignIO.read(f"{here.parent}/examples/simple.fa", "fasta")
-        use_log = False
-
-        keep_msa, trim_msa = create_msa(alignment, True)
-
-        ## execution
-        keep_msa, trim_msa = trim(
-            gappyness,
-            site_classification_type,
-            site_classification_counts,
-            keep_msa,
-            trim_msa,
-            i,
-            gaps_threshold,
-            alignment,
-            TrimmingMode.kpic_gappy,
-            use_log,
-        )
-
-        ## check results
-        expected_keep_data = {
-            "1": np.array([b"", b"", b"", b"", b"", b""]),
-            "2": np.array([b"", b"", b"", b"", b"", b""]),
-            "3": np.array([b"", b"", b"", b"", b"", b""]),
-            "4": np.array([b"", b"", b"", b"", b"", b""]),
-            "5": np.array([b"", b"", b"", b"", b"", b""]),
-        }
-        expected_trim_data = {
-            "1": np.array([b"", b"", b"", b"T", b"", b""]),
-            "2": np.array([b"", b"", b"", b"-", b"", b""]),
-            "3": np.array([b"", b"", b"", b"-", b"", b""]),
-            "4": np.array([b"", b"", b"", b"-", b"", b""]),
-            "5": np.array([b"", b"", b"", b"-", b"", b""]),
-        }
-
-        assert expected_keep_data.keys() == keep_msa._data.keys()
-        assert all(
-            np.array_equal(expected_keep_data[key], keep_msa._data[key])
-            for key in expected_keep_data
-        )
-        assert expected_trim_data.keys() == trim_msa._data.keys()
-        assert all(
-            np.array_equal(expected_trim_data[key], trim_msa._data[key])
-            for key in expected_trim_data
-        )