Rename to schemarecomb.

Author: bbremer

README.rst

@@ -1,8 +1,8 @@
-With ggrecomb, you can design easy-to-use recombinant protein libraries, even if you aren't a computational expert.
+With schemarecomb, you can design easy-to-use chimeric protein libraries, even if you aren't a computational expert.
 
 Here's a simple example::
 
-  >>> import ggrecomb as sr
+  >>> import schemarecomb as sr
   >>> from Bio import SeqIO
   >>>
   >>> # pytest stuff, you can ignore this.
@@ -24,11 +24,10 @@ Here's a simple example::
   >>> best_lib = max(libraries, key=lambda x: x.mutation_rate - x.energy)
   >>>
   >>> # Save the generated DNA fragments.
-  >>> # out_fn = tempdir + '/' + 'bgl3_dna_frags.fasta'
   >>> SeqIO.write(best_lib.dna_blocks, out_fn, 'fasta')
   42
 
-With this simple script, we generated a six parent, seven block chimeric beta-glucosidase library. The saved DNA fragments can be ordered directly from a DNA synthesis provider and assembled with `NEB's Golden Gate Assembly Kit <https://www.neb.com/products/e1601-neb-golden-gate-assembly-mix>`_. There's no worrying about adding restriction sites since ggrecomb automatically adds BsaI sites.
+With this simple script, we generated a six parent, seven block chimeric beta-glucosidase library. The saved DNA fragments can be ordered directly from a DNA synthesis provider and assembled with `NEB's Golden Gate Assembly Kit <https://www.neb.com/products/e1601-neb-golden-gate-assembly-mix>`_. There's no worrying about adding restriction sites since schemarecomb automatically adds BsaI sites.
 
 
 Why Recombinant Proteins?
@@ -38,23 +37,23 @@ Engineering proteins with recombinant libraries has a number of advantages over
 
 So why doesn't everybody do recombinant protein engineering? Historically, there's a number of technical challenges that made recombinant libraries impractical for general use. Namely, a great deal of computational expertise and time is needed to manually generate and select suitable libraries. Even with the required computational resources, mutagenesis was significantly easier than assembling 8+ DNA fragments when protein engineering was developing its fundamentals, so nearly everybody opted for traditional directed evolution and passed that practice down to their students and mentees.
 
-The goal of this software package is to make recombinant library design accessible and convenient for protein engineers of all computational skill levels. ggrecomb designs libraries that come ready to order and construct with a simple Golden Gate Assembly reaction. To learn more, read the `ggrecomb documentation <https://ggrecomb.readthedocs.io/en/latest/>`_.
+The goal of this software package is to make recombinant library design accessible and convenient for protein engineers of all computational skill levels. schemarecomb designs libraries that come ready to order and construct with a simple Golden Gate Assembly reaction. To learn more, read the `schemarecomb documentation <https://schemarecomb.readthedocs.io/en/latest/>`_.
 
 
 Installation
 ------------
 
 .. code-block:: bash
 
-    $ pip install ggrecomb
+    $ pip install schemarecomb
 
 
 Documentation
 -------------
 
 Package reference material and helpful guides can be found at:
 
-    https://ggrecomb.readthedocs.io/en/latest/
+    https://schemarecomb.readthedocs.io/en/latest/
 
 
 Citing
@@ -63,6 +62,6 @@ Citing
 ..
     https://www.software.ac.uk/how-cite-software?_ga=1.54830891.1882560887.1489012280
 
-If you use ggrecomb in a scientific publication, please cite it as::
+If you use schemarecomb in a scientific publication, please cite it as::
 
-    Bremer, B. & Romero, P. (2021). ggrecomb [Software]. Available from https://github.com/RomeroLab/ggrecomb.
+    Bremer, B. & Romero, P. (2021). schemarecomb [Software]. Available from https://github.com/RomeroLab/schemarecomb.

bin/ggrecomb bin/schemarecomb

@@ -8,7 +8,7 @@
 from Bio import SeqIO
 import pytest
 
-import ggrecomb
+import schemarecomb
 
 
 @pytest.fixture
@@ -199,7 +199,8 @@ def rid_to_database(http_dir):
     for database, date in database_query_dates.items():
         fn = http_dir / f'blast_{database}_put_{date}.txt'
         with open(fn, 'rb') as handle:
-            rid, _ = ggrecomb.parent_alignment._parse_qblast_ref_page(handle)
+            rid, _ = schemarecomb.parent_alignment._parse_qblast_ref_page(
+                handle)
         if database == 'refseq':
             # Patch because refseq filename does not match database query name
             database = 'refseq_protein'
@@ -266,9 +267,9 @@ def bgl3_records_aln(fixture_dir):
 
 @pytest.fixture
 def bgl3_parents_aln(bgl3_pdb_filename, bgl3_records_aln):
-    pdb = ggrecomb.PDBStructure.from_pdb_file(bgl3_pdb_filename)
-    parents = ggrecomb.ParentSequences(bgl3_records_aln, pdb_structure=pdb,
-                                       prealigned=True)
+    pdb = schemarecomb.PDBStructure.from_pdb_file(bgl3_pdb_filename)
+    parents = schemarecomb.ParentSequences(bgl3_records_aln, pdb_structure=pdb,
+                                           prealigned=True)
     return parents
 
 
@@ -292,8 +293,9 @@ def bgl3_single_aln_str(fixture_dir):
 
 @pytest.fixture
 def bgl3_parent_alignment(bgl3_records_aln, bgl3_pdb_filename):
-    pdb = ggrecomb.PDBStructure.from_pdb_file(bgl3_pdb_filename)
-    parents = ggrecomb.ParentSequences(bgl3_records_aln, pdb, prealigned=True)
+    pdb = schemarecomb.PDBStructure.from_pdb_file(bgl3_pdb_filename)
+    parents = schemarecomb.ParentSequences(bgl3_records_aln, pdb,
+                                           prealigned=True)
     return parents
 
 
@@ -306,8 +308,9 @@ def mock_bgl3_blast_query(bgl3_records, mocker, blast_http_responses,
 
     This:
         fake_urlopen, fake_efetch = mock_bgl3_blast_query
-        mocker.patch('ggrecomb.parent_alignment.urlopen', fake_urlopen)
-        mocker.patch('ggrecomb.parent_alignment.Entrez.efetch', fake_efetch)
+        mocker.patch('schemarecomb.parent_alignment.urlopen', fake_urlopen)
+        mocker.patch('schemarecomb.parent_alignment.Entrez.efetch',
+                     fake_efetch)
 
     is equivalent to this:
         query_seq = str(bgl3_records[0].seq)
@@ -316,7 +319,7 @@ def mock_bgl3_blast_query(bgl3_records, mocker, blast_http_responses,
         responses = {'refseq_protein': refseq_responses,
                      'pdbaa': pdb_responses}
         mocker.patch(
-            'ggrecomb.parent_alignment.urlopen',
+            'schemarecomb.parent_alignment.urlopen',
             wrap_urlopen(
                 query_seq=query_seq,
                 parents_aln_str=bgl3_parents_aln_str,
@@ -326,7 +329,7 @@ def mock_bgl3_blast_query(bgl3_records, mocker, blast_http_responses,
         )
         # also need to patch Entrez.efetch for BLAST runs
         mocker.patch(
-            'ggrecomb.parent_alignment.Entrez.efetch',
+            'schemarecomb.parent_alignment.Entrez.efetch',
             wrap_efetch(
                 responses=responses,
                 acc_to_database=acc_to_database
@@ -356,8 +359,8 @@ def mock_bgl3_blast_query(bgl3_records, mocker, blast_http_responses,
 @pytest.fixture
 def bgl3_mock_namespace(doctest_namespace, mocker, mock_bgl3_blast_query):
     fake_urlopen, fake_efetch = mock_bgl3_blast_query
-    mocker.patch('ggrecomb.parent_alignment.urlopen', fake_urlopen)
-    mocker.patch('ggrecomb.parent_alignment.Entrez.efetch', fake_efetch)
+    mocker.patch('schemarecomb.parent_alignment.urlopen', fake_urlopen)
+    mocker.patch('schemarecomb.parent_alignment.Entrez.efetch', fake_efetch)
 
 
 @pytest.fixture

conftest.py

@@ -17,7 +17,7 @@
 
 # -- Project information -----------------------------------------------------
 
-project = 'ggrecomb'
+project = 'schemarecomb'
 copyright = '2021, Bennett Bremer'
 author = 'Bennett Bremer'
 
@@ -69,7 +69,7 @@
 
 
 def setup(app):
-    import ggrecomb as sr
+    import schemarecomb as sr
     # need to assign the names here, otherwise autodoc won't document these
     # classes, and will instead just say 'alias of ...'
     sr.generate_libraries.__name__ = 'generate_libraries'

doc/source/conf.py

@@ -1,44 +1,49 @@
-.. ggrecomb documentation master file, created by
+.. schemarecomb documentation master file, created by
    sphinx-quickstart on Thu Jul 29 16:15:20 2021.
    You can adapt this file completely to your liking, but it should at least
    contain the root `toctree` directive.
 
-Welcome to ggrecomb's documentation!
-====================================
+Welcome to schemarecomb's documentation!
+========================================
 
-With ggrecomb, you can design easy-to-use recombinant protein libraries, even if you aren't a computational expert.
+With schemarecomb, you can design easy-to-use recombinant protein libraries, even if you aren't a computational expert.
 
 
 Usage
 -----
 
 ..
-  ggrecomb provides the flexibility to customize recombinant library design with a number of options. Check out the :ref:`Biologist's Guide<biologists>` if you're comfortable with recombinant protein library design but want to be guided through using the library. Conversely, users with computational expertise but limited biological experience should read the :ref:`Programmer's Guide<programmers>`. Finally, if you know what you're doing, glance at the :ref:`Quickstart <quickstart>` document and look at the :ref:`Reference Manual<reference>` as needed.
+  schemarecomb provides the flexibility to customize recombinant library design with a number of options. Check out the :ref:`Biologist's Guide<biologists>` if you're comfortable with recombinant protein library design but want to be guided through using the library. Conversely, users with computational expertise but limited biological experience should read the :ref:`Programmer's Guide<programmers>`. Finally, if you know what you're doing, glance at the :ref:`Quickstart <quickstart>` document and look at the :ref:`Reference Manual<reference>` as needed.
 
 
 Here's a simple example::
 
-  import ggrecomb
-
-  # Specify library parameters.
-  parent_fn = 'P450_sequences.fasta'  # parent_file: 3 parents
-  num_blocks = 8  # number of blocks in chimeras
-  min_block_len = 40  # min length of chimeric blocks
-  max_block_len = 80  # max length of chimeric blocks
-
-  # Create a parent alignment and get the closest PDB structure.
-  parents = ggrecomb.ParentSequences.from_fasta(parent_fn, auto_align=True)
-  parents.get_PDB()
-
-  # Run SCHEMA-RASPP to get libraries.
-  raspp = ggrecomb.RASPP(parents, num_blocks)
-  libraries = raspp.vary_m_proxy(min_block_len, max_block_len)
-
-  # Auto-select the best library and save the resulting DNA fragments.
-  best_lib = ggrecomb.LibSelector.auto(libraries)
-  best_lib.save('library_dna_fragments.fasta')
-
-With this simple script, we generated a three parent, eight block chimeric P450 library. The saved DNA fragments can be ordered directly from a DNA synthesis provider and assembled with `NEB's Golden Gate Assembly Kit <https://www.neb.com/products/e1601-neb-golden-gate-assembly-mix>`_. There's no worrying about adding restriction sites since ggrecomb automatically adds BsaI sites.
+  >>> import schemarecomb as sr
+  >>> from Bio import SeqIO
+  >>>
+  >>> # pytest stuff, you can ignore this.
+  >>> getfixture('bgl3_mock_namespace')
+  >>> tempdir = getfixture('tmpdir')  #doctest: +ELLIPSIS
+  >>> out_fn = tempdir / 'bgl3_dna_frags.fasta'
+  >>>
+  >>> # Create a parent alignment and get the closest PDB structure.
+  >>> fn = 'tests/fixtures/bgl3_1-parent/bgl3_p0.fasta'
+  >>> parents = sr.ParentSequences.from_fasta(fn)
+  >>> parents.obtain_seqs(6, 0.7)  # BLAST takes about 10 minutes.
+  >>> parents.align()  # MUSCLE takes about a minute.
+  >>> parents.get_PDB()  # BLAST takes about 10 minutes.
+  >>>
+  >>> # Run SCHEMA-RASPP to get libraries.
+  >>> libraries = sr.generate_libraries(parents, 7)
+  >>>
+  >>> # Auto-select the best library and save the resulting DNA fragments.
+  >>> best_lib = max(libraries, key=lambda x: x.mutation_rate - x.energy)
+  >>>
+  >>> # Save the generated DNA fragments.
+  >>> SeqIO.write(best_lib.dna_blocks, out_fn, 'fasta')
+  42
+
+With this simple script, we generated a six parent, seven block chimeric beta-glucosidase library. The saved DNA fragments can be ordered directly from a DNA synthesis provider and assembled with `NEB's Golden Gate Assembly Kit <https://www.neb.com/products/e1601-neb-golden-gate-assembly-mix>`_. There's no worrying about adding restriction sites since schemarecomb automatically adds BsaI sites.
 
 View the :ref:`Quickstart Guide <quickstart>` for more example scripts and the :ref:`Reference Manual <reference>` for more details on specific classes and modules.
 

doc/source/index.rst

@@ -10,25 +10,25 @@ Quickstart
 
 To get started, you'll need a FASTA file with one or more parent amino acid sequences. If desired, we can find additional parents with BLAST.
 
-Optionally, you can provide a PDB structure file, but otherwise we'll find one that matches the first parent sequence you provided. See :class:`ggrecomb.PDBStructure` for more details.
+Optionally, you can provide a PDB structure file, but otherwise we'll find one that matches the first parent sequence you provided. See :class:`schemarecomb.PDBStructure` for more details.
 
 .. note::
 
-    This guide assumes you're using Python 3.9 on Linux. If you use MacOS, things will probably work the same, but no guarantees. If you have Windows, I recommend you use the `Windows Subsystem for Linux  <https://docs.microsoft.com/en-us/windows/wsl/install-win10>`_, but again, no guarantees. Please raise an issue on the ggrecomb GitHub page if you have OS difficulty.
+    This guide assumes you're using Python 3.9 on Linux. If you use MacOS, things will probably work the same, but no guarantees. If you have Windows, I recommend you use the `Windows Subsystem for Linux  <https://docs.microsoft.com/en-us/windows/wsl/install-win10>`_, but again, no guarantees. Please raise an issue on the schemarecomb GitHub page if you have OS difficulty.
 
 
-1. Install ggrecomb
--------------------
+1. Install schemarecomb
+-----------------------
 
-ggrecomb is available on pip::
+schemarecomb is available on pip::
 
-    $ pip install ggrecomb
+    $ pip install schemarecomb
 
-Or you can install ggrecomb from source. See :ref:`Installation<install>` for more information.
+Or you can install schemarecomb from source. See :ref:`Installation<install>` for more information.
 
-In a Python script, import ggrecomb::
+In a Python script, import schemarecomb::
 
-    import ggrecomb
+    import schemarecomb
 
 
 2. Make a ParentSequences
@@ -37,35 +37,35 @@ In a Python script, import ggrecomb::
 Load your parent FASTA file and find additional parents if needed. For this example, we'll use beta-glucosidase (bgl3, PDB ID 1GNX)::
 
     parent_fn = 'bgl3.fasta'
-    p_aln = ggrecomb.ParentSequences.from_fasta(parent_fn)
-    p_aln.obtain_seqs(num_final_seqs=4, desired_indentity=0.7)
+    p_aln = schemarecomb.ParentSequences.from_fasta(parent_fn)
+    p_aln.obtain_seqs(num_final_seqs=4, desired_identity=0.7)
+    p_aln.get_PDB()
 
-After running, p_aln is a ParentSequences with four parents that have about 70% pairwise idenity.
+After running, p_aln is a ParentSequences with four parents that have about 70% pairwise identity and the closest PDB structure.
 
-See :class:`ggrecomb.ParentSequences` for more options.
+See :class:`schemarecomb.ParentSequences` for more options. Viewing :class:`schemarecomb.PDBStructure` may also be helpful.
 
 
 3. Run the SCHEMA-RASPP algorithm
 ---------------------------------
 
 SCHEMA-RASPP finds potential libraries and calculates the probability of Golden Gate assembly for each::
 
-    raspp = ggrecomb.RASPP(p_aln, 5)
-    libraries = raspp.vary_m_proxy(60, 100)
+    libraries = schemarecomb.generate_libraries(p_aln, 6)
 
-This finds libraries with six blocks (five breakpoints) with block sizes between 60 and 100 amino acids.
+This finds libraries with six blocks (five breakpoints).
 
-See ggrecomb.RASPP (TODO: make this link after refactoring PA docstring) for more options.
+See :func:`schemarecomb.generate_libraries` for more options.
 
 
 4. Select and save a library
 ----------------------------
 
-Let RASPP automatically select a library::
+Select the library with highest mutation_rate - energy and save generated DNA blocks::
 
-    best_lib = ggrecomb.LibSelector.auto(libraries)
-    best_lib.save('bgl3_library_dna.fasta')
+    best_lib = max(libraries, key=lambda x: x.mutation_rate - x.energy)
+    SeqIO.write(best_lib.dna_blocks, 'bgl3_library_dna.fasta', 'fasta')
 
 The DNA fragments in FASTA format in a file named "bgl3_library_dna.fasta". These fragments are ready to order and assemble with `NEB's Golden Gate Assembly Kit <https://www.neb.com/products/e1601-neb-golden-gate-assembly-mix>`_. You can simulate the Golden Gate reaction using SnapGene.
 
-See ggrecomb.LibSelector for more options.
+See :class:`schemarecomb.Library` for more options.

doc/source/quickstart.rst

@@ -5,7 +5,7 @@
 Reference Manual
 ****************
 
-.. currentmodule:: ggrecomb
+.. currentmodule:: schemarecomb
 
 
 Primary Classes and Functions

doc/source/reference.rst

@@ -1,5 +1,5 @@
 [tool.poetry]
-name = 'ggrecomb'
+name = 'schemarecomb'
 version = '0.0.4'
 description = 'Design recombinant protein libraries for Golden Gate Assembly.'
 authors = ['Bennett Bremer <[email protected]>']
@@ -18,23 +18,23 @@ sphinx = '^4.0.1'
 sphinx-autodoc-typehints = '^1.12.0'
 
 [tool.poetry.urls]
-"Download" = "https://pypi.org/project/ggrecomb"
-"Source Code" = "https://github.com/RomeroLab/ggrecomb"
-"Documentation" = "https://ggrecomb.readthedocs.io/en/latest"
+"Download" = "https://pypi.org/project/schemarecomb"
+"Source Code" = "https://github.com/RomeroLab/schemarecomb"
+"Documentation" = "https://schemarecomb.readthedocs.io/en/latest"
 
 [tool.pytest.ini_options]
 addopts = "--doctest-modules"
 doctest_optionflags = "ELLIPSIS"
 testpaths = [
     "tests/unit/",
-    "src/ggrecomb/libraries.py",
-    "src/ggrecomb/pdb_structure.py",
-    "src/ggrecomb/parent_alignment.py",
+    "src/schemarecomb/libraries.py",
+    "src/schemarecomb/pdb_structure.py",
+    "src/schemarecomb/parent_alignment.py",
     "README.rst"
 ]
 
 # [tool.poetry.scripts]
-# ggrecomb = {reference = "bin/ggrecomb", type="file"}
+# schemarecomb = {reference = "bin/schemarecomb", type="file"}
 
 [build-system]
 requires = ["poetry-core>=1.1.0a5"]

pyproject.toml

@@ -1,7 +1,7 @@
-from ggrecomb.pdb_structure import _PDBStructure as PDBStructure
-from ggrecomb.parent_alignment import _ParentSequences as ParentSequences
-from ggrecomb.libraries import _Library as Library
-from ggrecomb.optimizers import _generate_libraries as generate_libraries
+from schemarecomb.pdb_structure import _PDBStructure as PDBStructure
+from schemarecomb.parent_alignment import _ParentSequences as ParentSequences
+from schemarecomb.libraries import _Library as Library
+from schemarecomb.optimizers import _generate_libraries as generate_libraries
 
 from . import energy_functions
 from . import restriction_enzymes

src/ggrecomb/__init__.py src/schemarecomb/__init__.py

@@ -1,10 +1,10 @@
-"""Recombination site discovery in :class:`~ggrecomb.ParentSequences`."""
+"""Recombination site discovery in :class:`~schemarecomb.ParentSequences`."""
 
 import itertools
 from typing import NamedTuple
 from typing import Optional
 
-from ggrecomb import ParentSequences
+from schemarecomb import ParentSequences
 
 
 class Overhang(NamedTuple):