def get_all_possible_binary(mutations,encoding_table,skip_sanity_checks=False):
"""
Get the complete set of binary genotypes possible given a mutations list
and an encoding table. There is no particular order to the genotypes.
Consider sorting.
mutations : list
Mutation list encoding possible states at each site. If this is
not specified, this will be generated automatically based on the states
seen in the list of genotypes.
encoding_table : pandas.DataFrame
DataFrame that encodes the binary representation of each mutation in
the list of genotypes. (See the `get_encoding_table` function).
skip_sanity_checks : bool
whether or not to check sanity of inputs (default: False)
Returns
-------
all_possible_binary : list
list of all possible binary genotypes given mutations list and
encoding_table
"""
if not skip_sanity_checks:
check.mutations_sanity(mutations)
all_possible = mutations_to_genotypes(mutations,skip_sanity_checks=True)
all_possible_binary = genotypes_to_binary(all_possible,
encoding_table,
skip_sanity_checks=True)
return all_possible_binary
def mutations_to_genotypes(mutations,skip_sanity_checks=False):
"""
Use a mutations list to construct an array of genotypes composed
of the mutations.
Parameters
----------
mutations : list
List of lists containing allowable mutations at each site.
skip_sanity_checks : bool
whether or not to check sanity of inputs (default: false)
Returns
-------
genotype : list
list of genotypes comprised of all combinations of mutations in
mutations list
"""
if not skip_sanity_checks:
check.mutations_sanity(mutations)
sequences = itertools.product(*mutations)
genotype = ["".join(s) for s in sequences]
return genotype
def genotype_is_in(genotypes,mutations,skip_sanity_checks=False):
"""
Determine whether genotypes are within the volume covered by mutations list.
Parameters
----------
genotypes : str or list of str
genotype(s) to check.
mutations : list
List of lists containing allowable mutations at each site.
skip_sanity_checks : bool
whether or not to check sanity of inputs (default: false)
Returns
-------
result : bool or list of bool
whether genotypes are contained within the GenotypePhenotypeMap
"""
# If a single genotype, convert to a list
if type(genotypes) is str:
genotypes = [genotypes]
# Check sanity of mutations
if not skip_sanity_checks:
check.mutations_sanity(mutations)
# Default to not in
out = [False for _ in range(len(genotypes))]
for i, g in enumerate(genotypes):
try:
# if genotype wrong length, not in
if len(g) != len(mutations):
continue
# If genotype has state not in mutations, it's not in
good = True
for j in range(len(mutations)):
if g[j] not in mutations[j]:
good = False
break
out[i] = good
except TypeError:
err = f"Problem with genotype '{g}'\n"
err += "genotype must be a single str (one genotype) or list of \n"
err += "strings (multiple genotypes)\n"
raise TypeError(err)
return out
def get_missing_genotypes(genotype,mutations=None,skip_sanity_checks=False):
"""
Get a list of genotypes not found in the given genotype list.
Parameters
----------
genotype : list
List of genotypes.
mutations : list
Mutation list encoding possible states at each site. If this is
not specified, this will be generated automatically based on the states
seen in genotype.
skip_sanity_checks : bool
whether or not to check sanity of inputs (default: false)
Returns
-------
missing_genotype : list
list of all possible genotypes not found in genotypes list.
"""
# Check input sanity
if not skip_sanity_checks:
check.genotype_sanity(genotype)
if mutations is not None:
check.mutations_sanity(mutations,genotype=genotype)
# Construct a list of mutations. Skip sanity check -- we already validated
# or skipped.
if mutations is None:
mutations = genotypes_to_mutations(genotype,
skip_sanity_checks=True)
# Get all genotypes.
all_genotype = mutations_to_genotypes(mutations,skip_sanity_checks=True)
# Find genotypes not found in genotypes list.
missing_genotype = set(all_genotype) - set(genotype)
return list(missing_genotype)
def mutations(self,mutations):
"""
Set the mutations. This triggers reconstruction of binary etc.
Parameters
----------
mutations : list
List of list mapping sites to possible states at each site.
"""
if mutations is None:
mutations = utils.genotypes_to_mutations(self._data.loc[:,"genotype"],
wildtype=self._wildtype)
check.mutations_sanity(mutations,self._wildtype,self._data.loc[:,"genotype"])
is_different = False
for i in range(len(mutations)):
if set(mutations[i]) != set(self._mutations[i]):
is_different = True
break
if is_different:
self._mutations = mutations
self._rebuild_map()
def get_all_possible_genotypes(mutations,skip_sanity_checks=False):
"""
Get the complete set of genotypes possible given a mutations list. There is
no particular order to the genotypes. Consider sorting.
Parameters
----------
mutations : list
Mutation list encoding possible states at each site.
skip_sanity_checks : bool
whether or not to check sanity of inputs (default: false)
Returns
-------
genotype : list
list of all genotypes possible given the mutations list
"""
if not skip_sanity_checks:
check.mutations_sanity(mutations)
# Get all genotype.
return mutations_to_genotypes(mutations,skip_sanity_checks=True)
def __init__(self,
genotype=[],
wildtype=None,
mutations=None,
site_labels=None,
**kwargs):
# If no wildtype is specified, use the first genotype as the wildtype
# sequence.
if wildtype is None:
if len(genotype) > 0:
wildtype = genotype[0]
else:
err = "You must specify at least the wildtype sequence or a \n"
err += "a genotype array with at least one entry\n"
raise ValueError(err)
# Check sanity of wildtype
check.wildtype_sanity(wildtype)
# Check genotypes sanity
check.genotype_sanity(genotype,wildtype=wildtype)
# Construct mutations list if not specified
if mutations is None:
mutations = utils.genotypes_to_mutations(genotype,
wildtype=wildtype)
# Check mutations sanity
check.mutations_sanity(mutations,
wildtype=wildtype,
genotype=genotype)
# Construct site_labels list if not specified
if site_labels is None:
site_labels = list(range(len(wildtype)))
# Check site_labels sanity
check.site_labels_sanity(site_labels,wildtype=wildtype)
# Start loading in the data from above
self._wildtype = wildtype
self._mutations = mutations
self._site_labels = site_labels
# Construct the master data frame for the gpmap.
self._data = pd.DataFrame({"genotype":genotype})
# --------------------------------------------------------------------
# kwargs; interpreted as columns in the dataframe
for k in kwargs:
# Make sure the keyword is not already an attribute of self
try:
self.__getattribute__(k)
err = f"keyword '{k}' is a reserved name. Please choose a\n"
err += "different name for this column.\n"
raise ValueError(err)
except AttributeError:
pass
# Make sure we're not going to collide with a private name we
# cannot guarantee won't exist in the future...
if k[0] in ["_","."]:
err = "data keywords cannot start with '_' or '.'\n"
raise ValueError(err)
# Make sure the kwarg has the same length as the genotypes
try:
if len(kwargs[k]) != len(genotype):
raise TypeError
except TypeError:
err = "keyword arguments must specify data as an array-like\n"
err += "data structure with the same length as the genotype\n"
err += "array.\n"
raise ValueError(err)
# Passed quality control, load into main data frame
self._data.loc[:,k] = kwargs[k]
# Set all rows to "include" = True
self._data.loc[:,"include"] = np.ones(len(genotype),dtype=bool)
# Make set of current genotypes
self._current_genotype = self._data.loc[:,"genotype"].copy()
# Build encoding table and binary representation of map
self._rebuild_map()
def test_check_mutations_sanity():
"""
Test mutations sanity checker.
"""
# Not a list of lists
with pytest.raises(ValueError):
check.mutations_sanity([5,5])
# Dict, not indexable by 0
with pytest.raises(ValueError):
check.mutations_sanity({"1":["A"]})
# Should fail because it's a dict, even if indexable properly
with pytest.raises(ValueError):
check.mutations_sanity({0:["A"],1:["B"]})
# Empty list value
with pytest.raises(ValueError):
check.mutations_sanity([[],["A"]])
# mismatch with wildtype
with pytest.raises(ValueError):
check.mutations_sanity([["A","B"]],wildtype="AA")
# should not throw error
check.mutations_sanity([["A","B"]])
check.mutations_sanity([["A","B"]],wildtype="A")
# Die because genotype has character ("C") that is not in the mutations
with pytest.raises(ValueError):
check.mutations_sanity([["A","B"]],wildtype="A",genotype=["C"])
# Die because wildtype has character ("C") that is not in the mutations
with pytest.raises(ValueError):
check.mutations_sanity([["A","B"]],wildtype="C",genotype=["A"])
# This should work
check.mutations_sanity([["A","B"]],wildtype="A",genotype=["B"])
def get_encoding_table(wildtype, mutations, site_labels=None):
"""
This function constructs a lookup table (pandas.DataFrame) for mutations
in a given mutations list. This table encodes mutations with a binary
representation.
Parameters
----------
wildtype : str
string with wildtype sequence
mutations : list
mutation list of lists containing possible states at each site.
(Must be same length as wt sequence).
site_labels : list or None
list of labels for each site. If None, use sequential integers starting
at 0. If not none, list must have same length as wildtype, all entires
must be unique.
Returns
-------
df : pandas.DataFrame
dataframe holding various representations of the gp map.
Notes
-----
The table has the following columns:
+ genotype_index : this corresponds to the number counting across the
genotype (starting at zero and going to length - 1)
+ wildtype_letter : character for wildtype at this position
+ mutation_letter : character for mutation at this position (for wildtype
row, this will be same as wildtype_letter)
+ binary_repr : binary representation of this site. If there are two
characters at the genotype site (wildtype and mutant) this
will be "0" for wildtype and "1" for mutant. If there are
three characters (wildtype, mutant1, mutant2), this will be
"00", "10", "01" for wildtype, mutant1, and mutant2 rows
respectively. For wildtype and three mutants, this will be
"000", "100","010","001". This binary representation allows
this genotype phenotype map to be fed directly into the
epistasis package, which assumes each site is binary.
binary_index_start : start of region of binary string corresponding to this
gene site.
binary_index_stop : end of region of binary string corresponding to this
gene site.
mutation_index : counter that gives each amino acid state a unique number.
site_label : label for site. Used for constructing mutant names. For example,
for the mutant A73G, A would be the wildtype_letter, G would
be the mutation_letter, and 73 would be the site label. If not
specified by the user, the site label is a number counting from
zero. Otherwise, it is the user-specified label.
"""
check.wildtype_sanity(wildtype)
# Check mutations input
check.mutations_sanity(mutations,wildtype=wildtype)
# Make fake site labels if not specified
if site_labels is None:
site_labels = list(range(len(wildtype)))
check.site_labels_sanity(site_labels,wildtype)
# Initialize table
table = []
mutation_index_counter = 1
binary_index_counter = 0
for genotype_index, alphabet in enumerate(mutations):
# Set genotype_index as int
genotype_index = int(genotype_index)
# Create local alphabet copy where wildtype state is the first element
# regardless of its position in the alphabet.
local_alphabet = alphabet[:]
if local_alphabet[0] != wildtype[genotype_index]:
local_alphabet.remove(wildtype[genotype_index])
local_alphabet.insert(0,wildtype[genotype_index])
binary_size = len(local_alphabet) - 1
for i, a in enumerate(local_alphabet):
tmp_binary_repr = ["0" for _ in range(binary_size)]
if i == 0:
mutation_index = None
else:
mutation_index = mutation_index_counter
mutation_index_counter += 1
tmp_binary_repr[i-1] = "1"
binary_repr = "".join(tmp_binary_repr)
table.append(
dict(
genotype_index=genotype_index,
wildtype_letter=wildtype[genotype_index],
mutation_letter=a,
binary_repr=binary_repr,
binary_index_start=binary_index_counter,
binary_index_stop=binary_index_counter + binary_size,
mutation_index=mutation_index,
site_label=site_labels[genotype_index]
)
)
binary_index_counter += binary_size
# Turn table into DataFrame.
df = pd.DataFrame(table)
df.genotype_index = df.genotype_index.astype('Int64')
df.mutation_index = df.mutation_index.astype('Int64')
df.binary_index_start = df.binary_index_start.astype('Int64')
df.binary_index_stop = df.binary_index_stop.astype('Int64')
return df