def _test_secondary(obj_test: Screen, parameters: dict) -> bool:
try:
obj_test.secondary_mean(
**parameters) # pass dictionary as arguments of method
except Exception as e: # pylint: disable=broad-except
logging.exception(e)
print(traceback.format_exc())
return True
return False
def _test_differential_output(obj_test: Screen, parameters: dict) -> bool:
try:
obj_test.differential(
obj_test,
**parameters) # pass dictionary as arguments of method
except Exception as e: # pylint: disable=broad-except
logging.exception(e)
print(traceback.format_exc())
return True
return False
def _generate_aph_obj(self) -> Screen: # pylint: disable=no-self-use
"""
Create object for the aph dataset.
"""
aminoacids = list(DEMO_DATASETS['df_aph'].index)
start_position = DEMO_DATASETS['df_aph'].columns[0]
# Full sequence
sequence_aph = 'MIEQDGLHAGSPAAWVERLFGYDWAQQTIGCSDAAVFRLSAQGRPVLFVKTDLSGALNELQ' + 'DEAARLSWLATTGVPCAAVLDVVTEAGRDWLLLGEVPGQDLLSSHLAPAEKVSIMADAMRR' + 'LHTLDPATCPFDHQAKHRIERARTRMEAGLVDQDDLDEEHQGLAPAELFARLKARMPDGED' + 'LVVTHGDACLPNIMVENGRFSGFIDCGRLGVADRYQDIALATRDIAEELGGEWADRFLVLY' + 'GIAAPDSQRIAFYRLLDEFF' # pylint: disable=line-too-long
# Define secondary structure
secondary_aph: List[List[str]] = [
['L1'] * (11), ['α1'] * (16 - 11), ['L2'] * (22 - 16),
['β1'] * (26 - 22), ['L3'] * (34 - 26), ['β2'] * (40 - 34),
['L4'] * (46 - 40), ['β3'] * (52 - 46), ['L5'] * (58 - 52),
['α2'] * (72 - 58), ['L6'] * (79 - 72), ['β4'] * (85 - 79),
['L7'] * (89 - 85), ['β5'] * (95 - 89), ['L8'] * (99 - 95),
['β6'] * (101 - 99), ['L9'] * (107 - 101), ['α3'] * (131 - 107),
['L10'] * (135 - 131), ['α4'] * (150 - 135), ['L11'] * (158 - 150),
['α5'] * (163 - 158), ['L12'] * (165 - 163), ['α6'] * (177 - 165),
['L13'] * (183 - 177), ['β7'] * (187 - 183), ['L14'] * (191 - 187),
['α7'] * (194 - 191), ['L15'] * (1),
['β8'] * (199 - 195), ['L16'] * (201 - 199), ['β9'] * (206 - 201),
['L17'] * (212 - 206), ['β10'] * (216 - 212), ['α8'] * (245 - 216),
['L18'] * (4), ['α9'] * (264 - 249)
]
return Screen(datasets=np.log10(DEMO_DATASETS['df_aph']),
sequence=sequence_aph,
aminoacids=aminoacids,
start_position=start_position,
fillna=0,
secondary=secondary_aph)
def _generate_rev_obj(self) -> Screen: # pylint: disable=no-self-use
"""
Create object for the rev dataset.
"""
# Order of amino acid substitutions in the hras_enrichment dataset
aminoacids = list(DEMO_DATASETS['df_rev'].index)
start_position = DEMO_DATASETS['df_rev'].columns[0]
# Full sequence
sequence_rev = 'MAGRSGDSDEDLLKAVRLIKFLYQSNPPPNPEGTRQARRNRRRRWRERQRQIHSISERIL' + 'STYLGRSAEPVPLQLPPLERLTLDCNEDCGTSGTQGVGSPQILVESPTILESGAKE' # pylint: disable=line-too-long
# Define secondary structure
secondary_rev: List[List[str]] = [['L1'] * (8), ['α1'] * (25 - 8),
['L2'] * (33 - 25),
['α2'] * (68 - 33),
['L3'] * (116 - 41)]
return Screen(datasets=DEMO_DATASETS['df_rev'],
sequence=sequence_rev,
aminoacids=aminoacids,
start_position=start_position,
fillna=0,
secondary=secondary_rev)
def _generate_asynuclein_obj(self) -> Screen: # pylint: disable=no-self-use
"""
Create object for the synuclein dataset.
"""
# Order of amino acid substitutions in the hras_enrichment dataset
aminoacids = list(DEMO_DATASETS['df_asynuclein'].index)
start_position = DEMO_DATASETS['df_asynuclein'].columns[0]
# Full sequence
sequence_asynuclein = 'MDVFMKGLSKAKEGVVAAAEKTKQGVAEAAGKTKEGVLYVGSKTKEGVVHGVATVAEKTK' + 'EQVTNVGGAVVTGVTAVAQKTVEGAGSIAAATGFVKKDQLGKNEEGAPQEGILEDMPVDP' + 'DNEAYEMPSEEGYQDYEPEA' # pylint: disable=line-too-long
# Define secondary structure
secondary_asynuclein: List[List[str]] = [['L1'] * (1),
['α1'] * (37 - 1),
['L2'] * (44 - 37),
['α2'] * (92 - 44),
['L3'] * (140 - 92)]
return Screen(datasets=DEMO_DATASETS['df_asynuclein'],
sequence=sequence_asynuclein,
aminoacids=aminoacids,
start_position=start_position,
fillna=0,
secondary=secondary_asynuclein)
def _generate_tat_obj(self) -> Screen: # pylint: disable=no-self-use
"""
Create object for the tat dataset.
"""
# Order of amino acid substitutions in the hras_enrichment dataset
aminoacids = list(DEMO_DATASETS['df_tat'].index)
start_position = DEMO_DATASETS['df_tat'].columns[0]
# Full sequence
sequence_tat = 'MEPVDPRLEPWKHPGSQPKTACTNCYCKKCCFHCQVCFITKALGISYGRKKRRQRRRAHQ' + 'NSQTHQASLSKQPTSQPRGDPTGPKE' # pylint: disable=line-too-long
# Define secondary structure
secondary_tat: List[List[str]] = [['L1'] * (8), ['α1'] * (13 - 8),
['L2'] * (28 - 14),
['α2'] * (41 - 28),
['L3'] * (90 - 41)]
return Screen(datasets=DEMO_DATASETS['df_tat'],
sequence=sequence_tat,
aminoacids=aminoacids,
start_position=start_position,
fillna=0,
secondary=secondary_tat)
def _generate_ube2i_obj(self) -> Screen: # pylint: disable=no-self-use
"""
Create object for the ube2i dataset.
"""
# Order of amino acid substitutions in the hras_enrichment dataset
aminoacids = list(DEMO_DATASETS['df_ube2i'].index)
start_position = DEMO_DATASETS['df_ube2i'].columns[0]
# Full sequence
sequence_ube2i_x = 'MSGIALSRLAQERKAWRKDHPFGFVAVPTKNPDGTMNLMNWECAIPGKKGTP' + 'WEGGLFKLRMLFKDDYPSSPPKCKFEPPLFHPNVYPSGTVCLSILEEDKDWRPAITIKQ' + 'ILLGIQELLNEPNIQDPAQAEAYTIYCQNRVEYEKRVRAQAKKFAPS' # pylint: disable=line-too-long
# Define secondary structure
secondary_ube2i: List[List[str]] = [
['α1'] * (20 - 1), ['L1'] * (24 - 20), ['β1'] * (30 - 24),
['L2'] * 5, ['β2'] * (46 - 35), ['L3'] * (56 - 46),
['β3'] * (63 - 56), ['L4'] * (73 - 63), ['β4'] * (77 - 73),
['L5'] * (93 - 77), ['α2'] * (98 - 93), ['L6'] * (107 - 98),
['α3'] * (122 - 107), ['L7'] * (129 - 122), ['α4'] * (155 - 129),
['L8'] * (160 - 155)
]
# Create objects
return Screen(datasets=DEMO_DATASETS['df_ube2i'],
sequence=sequence_ube2i_x,
aminoacids=aminoacids,
start_position=start_position,
fillna=1,
secondary=secondary_ube2i)
def _generate_sumo_obj(self) -> Screen: # pylint: disable=no-self-use
"""
Create object for the sumo1 dataset.
"""
# Order of amino acid substitutions in the hras_enrichment dataset
aminoacids = list(DEMO_DATASETS['df_sumo1'].index)
start_position = DEMO_DATASETS['df_sumo1'].columns[0]
# Full sequence
sequence_sumo1 = 'MSDQEAKPSTEDLGDKKEGEYIKLKVIGQDSSEIHFKVKMTTHLKKLKESYCQRQGVPMN' + 'SLRFLFEGQRIADNHTPKELGMEEEDVIEVYQEQTGGHSTV' # pylint: disable=line-too-long
# Define secondary structure
secondary_sumo1: List[List[str]] = [['L0'] * (20), ['β1'] * (28 - 20),
['L1'] * 3, ['β2'] * (39 - 31),
['L2'] * 4, ['α1'] * (55 - 43),
['L3'] * (6), ['β3'] * (65 - 61),
['L4'] * (75 - 65),
['α2'] * (80 - 75),
['L5'] * (85 - 80),
['β4'] * (92 - 85),
['L6'] * (101 - 92)]
return Screen(datasets=DEMO_DATASETS['df_sumo1'],
sequence=sequence_sumo1,
aminoacids=aminoacids,
start_position=start_position,
fillna=1,
secondary=secondary_sumo1)
def _generate_bla_obj(self) -> Screen: # pylint: disable=no-self-use
"""
Create object for the beta lactamase dataset.
"""
# Order of amino acid substitutions in the hras_enrichment dataset
aminoacids: List[str] = list(DEMO_DATASETS['df_bla'].index)
start_position = DEMO_DATASETS['df_bla'].columns[0]
# Define sequence. If you dont know the start of the sequence, just add X's
sequence_bla_x = 'MSIQHFRVALIPFFAAFCLPVFAHPETLVKVKDAEDQLGARVGYIELDLNSGKILESFRP' + 'EERFPMMSTFKVLLCGAVLSRVDAGQEQLGRRIHYSQNDLVEYSPVTEKHLTDGMTVREL' + 'CSAAITMSDNTAANLLLTTIGGPKELTAFLHNMGDHVTRLDRWEPELNEAIPNDERDTTM' + 'PAAMATTLRKLLTGELLTLASRQQLIDWMEADKVAGPLLRSALPAGWFIADKSGAGERGS' + 'RGIIAALGPDGKPSRIVVIYTTGSQATMDERNRQIAEIGASLIKHW' # pylint: disable=line-too-long
# Define secondary structure
secondary_bla: List[List[str]] = [
['L0'] * 23, ['α1'] * (38 - 23), ['L1'] * 2, ['β1'] * (48 - 40),
['L2'] * 5, ['β2'] * (57 - 53), ['L3'] * (68 - 57),
['α2'] * (84 - 68),
['L4'] * (95 - 84), ['α3'] * (100 - 95), ['L5'] * (103 - 100),
['α4'] * (110 - 103), ['L6'] * (116 - 110), ['α5'] * (140 - 116),
['L7'] * (1), ['α6'] * (153 - 141), ['L8'] * (164 - 153),
['α7'] * (169 - 164), ['L9'] * (179 - 169), ['α8'] * (194 - 179),
['L10'] * 3, ['α9'] * (210 - 197), ['L11'] * (227 - 210),
['β3'] * (235 - 227), ['L12'] * (240 - 235), ['β4'] * (249 - 240),
['L13'] * (254 - 249), ['β5'] * (262 - 254), ['L14'] * (266 - 262),
['α10'] * (286 - 266)
]
return Screen(datasets=DEMO_DATASETS['df_bla'],
sequence=sequence_bla_x,
aminoacids=aminoacids,
start_position=start_position,
fillna=0,
secondary=secondary_bla)
def _test_screen_output(parameters: dict) -> bool:
try:
Screen(**parameters)
except Exception as e: # pylint: disable=broad-except
logging.exception(e)
print(traceback.format_exc())
return True
return False
def _generate_b11l5f_obj(self) -> Screen: # pylint: disable=no-self-use
"""
Create object for the aph dataset.
"""
# Order of amino acid substitutions in the hras_enrichment dataset
aminoacids = list(DEMO_DATASETS['df_b11l5f'].index)
# Sequence
sequence_b11l5f = 'CRAASLLPGTWQVTMTNEDGQTSQGQMHFQPRSPYTLDVKAQGTISDGRPI' + 'SGKGKVTCKTPDTMDVDITYPSLGNMKVQGQVTLDSPTQFKFDVTTSDGSKVTGTLQRQE' # pylint: disable=line-too-long
start_position = DEMO_DATASETS['df_b11l5f'].columns[0]
return Screen(datasets=DEMO_DATASETS['df_b11l5f'],
sequence=sequence_b11l5f,
aminoacids=aminoacids,
start_position=start_position,
fillna=0)
def _generate_mapk1_obj(self) -> Screen: # pylint: disable=no-self-use
"""
Create object for the mapk1 dataset.
"""
# Order of amino acid substitutions in the hras_enrichment dataset
aminoacids = list(DEMO_DATASETS['df_mapk1'].index)
start_position = DEMO_DATASETS['df_mapk1'].columns[0]
# Full sequence
sequence_mapk1_x = 'MAAAAAAGAGPEMVRGQVFDVGPRYTNLSYIGEGAYGMVCSAYDNVNKVRVAIK' + 'KISPFEHQTYCQRTLREIKILLRFRHENIIGINDIIRAPTIEQMKDVYIVQDLMETDLYKLLKTQ' + 'HLSNDHICYFLYQILRGLKYIHSANVLHRDLKPSNLLLNTTCDLKICDFGLARVADPDHDHTGFL' + 'TEYVATRWYRAPEIMLNSKGYTKSIDIWSVGCILAEMLSNRPIFPGKHYLDQLNHILGILGSPSQ' + 'EDLNCIINLKARNYLLSLPHKNKVPWNRLFPNADSKALDLLDKMLTFNPHKRIEVEQALAHPYLE' + 'QYYDPSDEPIAEAPFKFDMELDDLPKEKLKELIFEETARFQPGYRS' # pylint: disable=line-too-long
# Create objects
return Screen(datasets=DEMO_DATASETS['df_mapk1'],
sequence=sequence_mapk1_x,
aminoacids=aminoacids,
start_position=start_position,
fillna=0)
def _generate_hras_gapgef_object(self) -> Screen: # pylint: disable=no-self-use
"""
Create object hras_gapgef.
"""
# Define protein sequence
hras_sequence: str = 'MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGFLCVFAINNTKSFEDIHQYREQIKRVKDSDDVPMVLVGNKCDLAARTVESRQAQDLARSYGIPYIETSAKTRQGVEDAFYTLVREIRQHKLRKLNPPDESGPG' # pylint: disable=line-too-long
# Define secondary structure
secondary: List[List[str]] = [
['L0'], ['β1'] * (9 - 1), ['L1'] * (15 - 9), ['α1'] * (25 - 15),
['L2'] * (36 - 25), ['β2'] * (46 - 36), ['L3'] * (48 - 46),
['β3'] * (58 - 48), ['L4'] * (64 - 58), ['α2'] * (74 - 64),
['L5'] * (76 - 74), ['β4'] * (83 - 76), ['L6'] * (86 - 83),
['α3'] * (103 - 86), ['L7'] * (110 - 103), ['β5'] * (116 - 110),
['L8'] * (126 - 116), ['α4'] * (137 - 126), ['L9'] * (140 - 137),
['β6'] * (143 - 140), ['L10'] * (151 - 143), ['α5'] * (172 - 151),
['L11'] * (190 - 172)
]
return Screen(datasets=DEMO_DATASETS['array_hras_gapgef'],
sequence=hras_sequence,
aminoacids=list('ACDEFGHIKLMNPQRSTVWY*'),
secondary=secondary)
def create_anc_ras_object() -> Tuple[Screen, List[Tuple[int, int]]]:
"""
This dataset is not available since it is not published yet.
"""
ancras: str = 'MTEYKLVVVGGGGVGKSALTIQFIQSHFVDEYDPTIEDSYRKQVVIDDEVAILDILDTAGQEEYSAMREQYMRNGEGFLLVYSITDRSSFDEISTYHEQILRVKDTDDVPMVLVGNKADLESRAVSMQEGQNLAKQLNVPFIETSAKQRMNVDEAFYTLVRVVRRH'
hras: str = 'MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGFLCVFAINNTKSFEDIHQYREQIKRVKDSDDVPMVLVGNKCDLAARTVESRQAQDLARSYGIPYIETSAKTRQGVEDAFYTLVREIRQH'
secondary: list = [
['β1'] * (9 - 1), ['L1'] * (16 - 9), ['α1'] * (25 - 16), ['L2'] *
(37 - 25), ['β2'] * (46 - 37), ['L3'] * (49 - 46), ['β3'] * (58 - 49),
['L4'] * (65 - 58), ['α2'] * (74 - 65), ['L5'] * (77 - 74),
['β4'] * (83 - 77), ['L6'] * (87 - 83), ['α3'] * (103 - 87),
['L7'] * (111 - 103), ['β5'] * (116 - 111), ['L8'] * (127 - 116),
['α4'] * (137 - 127), ['L9'] * (141 - 137), ['β6'] * (143 - 141),
['L10'] * (152 - 143), ['α5'] * (173 - 152), ['L11'] * (189 - 173)
]
kwargs: dict = {'secondary': secondary}
aminoacids: List[str] = list('ACDEFGHIKLMNPQRSTVWY*')
map_sequence_changes: List[Tuple[int, int]] = []
for index, (i, j) in enumerate(zip(hras, ancras), start=1):
if not i == j:
map_sequence_changes.append((index, index))
return Screen(ANC_RAS_ENRICHMENT, ancras, aminoacids,
**kwargs), map_sequence_changes
secondary: list = [['β1'] * (9 - 1), ['L1'] * (16 - 9), ['α1'] * (25 - 16),
['L2'] * (37 - 25), ['β2'] * (46 - 37), ['L3'] * (49 - 46),
['β3'] * (58 - 49), ['L4'] * (65 - 58), ['α2'] * (74 - 65),
['L5'] * (77 - 74), ['β4'] * (83 - 77), ['L6'] * (87 - 83),
['α3'] * (103 - 87), ['L7'] * (111 - 103),
['β5'] * (116 - 111), ['L8'] * (127 - 116),
['α4'] * (137 - 127), ['L9'] * (141 - 137),
['β6'] * (143 - 141), ['L10'] * (152 - 143),
['α5'] * (173 - 152), ['L11'] * (189 - 173)]
kwargs: dict = {'secondary': secondary}
aminoacids: List[str] = list('ACDEFGHIKLMNPQRSTVWY*')
# Create objects
HRAS_166_GAP: Screen = Screen([HRas166_GAP_r0, HRas166_GAP_r1], hras,
aminoacids, **kwargs)
HRAS_166_RBD: Screen = Screen([HRas166_RBD_r0, HRas166_RBD_r1, HRas166_RBD_r2],
hras, aminoacids, **kwargs)
HRAS_166_GAPGEF: Screen = Screen([HRas166_GAPGEF_r0, HRas166_GAPGEF_r1], hras,
aminoacids, **kwargs)
HRAS_188_BAF3: Screen = Screen([HRas188_BaF3_r0, HRas188_BaF3_r1], hras,
aminoacids, **kwargs)
HRAS_180_GAP: Screen = Screen([HRas180_GAP_r0, HRas180_GAP_r1, HRas180_GAP_r3],
hras, aminoacids, **kwargs)
HRAS_180_RBD: Screen = Screen(
[HRas180_RBD_r0, HRas180_RBD_r1, HRas180_RBD_r2, HRas180_RBD_r3], hras,
aminoacids, **kwargs)
KRAS_165_GAP: Screen = Screen([KRas165_GAP_r0, KRas165_GAP_r1, KRas165_GAP_r2],
kras, aminoacids, **kwargs)
KRAS_165_RBD: Screen = Screen([KRas165_RBD_r0, KRas165_RBD_r1], kras,
aminoacids, **kwargs)
def run_demo(figure: FIGURE_OPTIONS = 'heatmap', show: bool = True) -> None:
"""
Performs a demonstration of the mutagenesis_visualization software.
Parameters
-----------
figure : str, default 'heatmap'
There are a few example plots that can be displayed to test the
package is working on your station. The options are 'heatmap',
'miniheatmap', 'mean', 'kernel', 'pca' 'position', 'secondary_mean',
'correlation', 'individual_correlation' and 'pymol'.
Check the documentation for more information.
show : boolean, default True
If True, will execute plt.show() for each figure.
"""
# Load enrichment scores
hras_enrichment_rbd: npt.NDArray = np.genfromtxt(HRAS_RBD_COUNTS_CSV, delimiter=',')
# Define protein sequence
hras_sequence: str = 'MTEYKLVVVGAGGVGKSALTIQLIQNHFVDEYDPTIEDSYRKQVVIDGETCLLDILDTAGQEEYSAMRDQYMRTGEGFLCVFAINNTKSFEDIHQYREQIKRVKDSDDVPMVLVGNKCDLAARTVESRQAQDLARSYGIPYIETSAKTRQGVEDAFYTLVREIRQHKLRKLNPPDESGPG' # pylint: disable=line-too-long
# Set aminoacids
aminoacids: List[str] = list('ACDEFGHIKLMNPQRSTVWY*')
# Define secondary structure
secondary: list = [['L0'],
['β1'] * (9 - 1), ['L1'] * (15 - 9), ['α1'] * (25 - 15), ['L2'] * (36 - 25),
['β2'] * (46 - 36), ['L3'] * (48 - 46), ['β3'] * (58 - 48),
['L4'] * (64 - 58), ['α2'] * (74 - 64), ['L5'] * (76 - 74),
['β4'] * (83 - 76), ['L6'] * (86 - 83), ['α3'] * (103 - 86),
['L7'] * (110 - 103), ['β5'] * (116 - 110), ['L8'] * (126 - 116),
['α4'] * (137 - 126), ['L9'] * (140 - 137), ['β6'] * (143 - 140),
['L10'] * (151 - 143), ['α5'] * (172 - 151), ['L11'] * (190 - 172)]
# Create object
hras_rbd: Screen = Screen(
datasets=hras_enrichment_rbd,
sequence=hras_sequence,
aminoacids=aminoacids,
secondary=secondary
)
if figure.lower() == 'heatmap':
# Create heatmap plot
hras_rbd.heatmap(
title='H-Ras 2-166', mask_selfsubstitutions=False, show_cartoon=True, show=show
)
elif figure.lower() == 'miniheatmap':
# Condensed heatmap
hras_rbd.miniheatmap(mask_selfsubstitutions=False, title='Wt residue H-Ras', show=show)
elif figure.lower() == 'mean':
# Mean enrichment by position
hras_rbd.enrichment_bar(
figsize=[6, 2.5], mode='mean', show_cartoon=True, yscale=[-2, 0.5], title='', show=show
)
elif figure.lower() == 'kernel':
# Plot kernel dist using sns.distplot.
hras_rbd.kernel(histogram=True, title='H-Ras 2-166', xscale=[-2, 1], show=show)
elif figure.lower() == 'pca':
# PCA by amino acid substitution
hras_rbd.pca(dimensions=(0, 1), figsize=(2, 2), adjustlabels=True, title='', show=show)
elif figure.lower() == 'position':
# Create plot for position 117
hras_rbd.position_bar(
position=117,
yscale=(-1.5, 0.8),
figsize=(3.5, 2),
title='Position 117',
output_file=None,
show=show,
)
elif figure.lower() == 'secondary_mean':
hras_rbd.secondary_mean(
yscale=[-1, 0],
figsize=[3, 2],
title='Mean of secondary motifs',
show=show,
show_error_bars=False,
)
elif figure.lower() == 'correlation':
# Correlation between amino acids
hras_rbd.correlation(colorbar_scale=[0.5, 1], title='Correlation', show=show)
elif figure.lower() == 'individual_correlation':
# Explained variability by amino acid
hras_rbd.individual_correlation(
yscale=[0, 0.6],
title='Explained variability by amino acid',
output_file=None,
show=show,
)
elif figure.lower() == 'pymol':
hras_rbd.pymol(PDB_5P21)
else:
raise NameError('Select a valid name for a demo figure.')
