def CLINVAR(gene_list, gene_name_list, gene_name_set):
"""
Searches the gene_condition_id database that is downloaded to computer.
From ClinVar
Source file from /pub/clinvar/
Parameter gene_list: a list of genes
Preconditon: gene_list is a list of genes
Parameter gene_name_list: a list of gene names
Preconditon: gene_name_list is a list of Gene names [str]
Parameter gene_name_set: a set of gene names (used for searching)
Preconditon: gene_name_set is a set of gene names
"""
print("Searching ClinVar")
filename = helper.edit_filename(
"gene_condition_source_id", "sibling", foldername='databases')
with open(filename, "r", encoding='utf-8') as f:
reader = csv.reader(f, dialect="excel", delimiter='\t')
for row in reader:
gene_name = row[1] + row[2]
if gene_name in gene_name_set:
ind = gene_name_list.index(gene_name)
gene = gene_list[ind]
gene.set_disease(row[4], gene_name, "ClinVar")
print("ClinVar database complete")
def OMIM(gene_list, gene_name_list, gene_name_set):
"""
This procedure searches the OMIM database (downloaded to computer)
Parameter gene_list: a list of genes
Preconditon: gene_list is a list of genes
Parameter gene_name_list: a list of gene names
Preconditon: gene_name_list is a list of Gene names [str]
Parameter gene_name_set: a set of gene names (used for searching)
Preconditon: gene_name_set is a set of gene names
"""
print("Searching the OMIM Database")
filename = helper.edit_filename(
"morbidmap.txt", "sibling", foldername='databases')
with open(filename, "r", encoding='utf-8') as f:
reader = csv.reader(f, dialect="excel", delimiter='\t')
for row in reader:
try:
gene_row_list = row[1].split(", ")
for gene_name in gene_row_list:
if gene_name in gene_name_set:
ind = gene_name_list.index(gene_name)
gene = gene_list[ind]
disease = row[0]
gene.set_disease(disease, gene_name, "OMIM")
except IndexError:
pass
print("OMIM database complete")
def CGD(gene_list, gene_name_list, gene_name_set):
"""
This procedure searches the Clinical Genome Database (download to computer
and convert to tab-delimited file) for information about disease
Parameter gene_list: a list of genes
Preconditon: gene_list is a list of genes
Parameter gene_name_list: a list of gene names
Preconditon: gene_name_list is a list of Gene names [str]
Parameter gene_name_set: a set of gene names (used for searching)
Preconditon: gene_name_set is a set of gene names
"""
print("Searching the Clinical genetics Database")
filename = helper.edit_filename(
"CGD.txt", "sibling", foldername='databases')
with open(filename, "r", encoding='utf-8') as f:
reader = csv.reader(f, dialect="excel", delimiter='\t')
for row in reader:
gene_name = row[0]
if gene_name in gene_name_set:
ind = gene_name_list.index(gene_name)
gene = gene_list[ind]
gene.set_disease(row[3], gene_name, "CGD")
print("CGD database complete")
def DisGeNet(gene_list, gene_name_list, gene_name_set):
"""
This procedure searches DisGeNet (download to computer and
and convert to tab-delimited file) for information about disease
Parameter gene_list: a list of genes
Preconditon: gene_list is a list of genes
Parameter gene_name_list: a list of gene names
Preconditon: gene_name_list is a list of Gene names [str]
Parameter gene_name_set: a set of gene names (used for searching)
Preconditon: gene_name_set is a set of gene names
"""
print("Searching DisGesNet")
filename = helper.edit_filename("all_gene_disease_associations.tsv", "sibling",
foldername='databases')
with open(filename, "r", encoding='utf-8') as f:
reader = csv.reader(f, dialect="excel", delimiter='\t')
for row in reader:
gene_name = row[1]
if gene_name in gene_name_set:
ind = gene_name_list.index(gene_name)
gene = gene_list[ind]
gene.set_disease(row[5], gene_name, "DisGeNet")
print("DisGeNet database complete")
def UniProt(gene_list, gene_name_list, get_info=True):
"""
This procedure searches UniProt human polymorphism and disease mutations
(download to computer) for information about disease.
Parameter gene_list: a list of genes
Preconditon: gene_list is a list of genes
Parameter gene_name_list: a list of gene names
Preconditon: gene_name_list is a list of Gene names [str]
Parameter gene_name_set: a set of gene names (used for searching)
Preconditon: gene_name_set is a set of gene names
Parameter get_info: a boolean that says whether UniProt should search the
web for dbSNP information
Preconditon: get_info is a bool
"""
if not get_info:
print("Searching UniProt. This takes a few seconds.")
else:
print("Searching UniProt for mutation info. This takes a few minutes.")
filename = helper.edit_filename(
"humsavar.txt", "sibling", foldername='databases')
with open(filename, "r") as g:
data = g.read()
start_time = time.time()
i = 0
for gene_name in gene_name_list:
if '\n' + gene_name + " " in data:
row_list = re.findall('\n' + gene_name + r" .+", data)
helper.time_elapsed(start_time)
for row in row_list:
if "Disease" in row:
disease_name = re.search(r"(rs\w+|-)\s+(.+)", row).group(2)
ind = gene_name_list.index(gene_name)
gene = gene_list[ind]
gene.set_disease(disease_name, gene_name,
"UniProt", get_info)
if get_info:
disease = gene.disease_list()[-1]
dbSNP = re.search(r"(rs\w+|-)", row).group(1)
aa_change = re.search(r"(p.\w+)", row).group(0)
disease.set_amino_change(aa_change)
disease.set_SNP(dbSNP)
disease.get_SNP_info()
if disease.has_full_info():
i = i + 1
if i == 6:
i = 0
time.sleep(random.uniform(0.5, 1.25))
helper.time_elapsed(start_time)
time.sleep(random.uniform(0.5, 1.25))
print("\nUniProt database complete")
def CLINVAR_nuc(gene_list, gene_name_list, gene_name_set):
"""
Searches the variant_summary database that is downloaded to computer.
From ClinVar
Source file from /pub/clinvar/
Parameter gene_list: a list of genes
Preconditon: gene_list is a list of genes
Parameter gene_name_list: a list of gene names
Preconditon: gene_name_list is a list of Gene names [str]
Parameter gene_name_set: a set of gene names (used for searching)
Preconditon: gene_name_set is a set of gene names
"""
print("Searching ClinVar")
filename = helper.edit_filename(
"variant_summary.txt", "sibling", foldername='databases')
with open(filename, "r", encoding='utf-8') as f:
reader = csv.reader(f, dialect="excel", delimiter='\t')
for row in reader:
gene_name = row[4]
gene_name_in_set = gene_name in gene_name_set
if gene_name_in_set:
snv = row[1] == 'single nucleotide variant'
pathogenic = row[6] == 'Pathogenic' or row[6] == 'Likely pathogenic'
GRCh38 = "GRCh38" == row[16]
germline = "germline" == row[15] or "germline/somatic" == row[15]
if snv and pathogenic and GRCh38 and germline:
disease_name = row[13]
chromosome = row[18]
position = int(row[19])
nucleotide = re.search(r":c.+(\w>\w)", row[2]).group(1)
try:
protein = re.search(r"\((p.\w+).", row[2]).group(1)
except:
protein = ''
if protein != '':
ind = gene_name_list.index(gene_name)
gene = gene_list[ind]
gene.set_disease(
disease_name, gene_name, "ClinVar", True)
disease = gene.disease_list()[-1]
disease.set_amino_change(protein)
disease.set_allele_change(nucleotide)
disease.set_chromosome(chromosome)
disease.set_position(position, 'GRCh38')
print("ClinVar database complete")
def paper_search(gene_list, gene_name_list, gene_name_set):
"""
This procedure searches the database 'zf_database.txt' for mutations that
affect ZF proteins.
This database was created by looking at the list of ZF proteins that had
mutation info, and looking for papers about those proteins. Each mutation
is sourced to know what paper it came from.
Parameter gene_list: a list of genes
Preconditon: gene_list is a list of genes
Parameter gene_name_list: a list of gene names
Preconditon: gene_name_list is a list of Gene names [str]
Parameter gene_name_set: a set of gene names (used for searching)
Preconditon: gene_name_set is a set of gene names
"""
print("Searching created tab file of mutations")
filename = helper.edit_filename('zf_database.txt', "sibling",
foldername='databases')
with open(filename, 'r', encoding='ISO-8859-1') as f:
next(f)
reader = csv.reader(f, dialect='excel', delimiter='\t')
for row in reader:
gene_name = row[0]
if gene_name in gene_name_set:
ind = gene_name_list.index(gene_name)
gene = gene_list[ind]
gene.set_disease(row[3], gene_name, row[8], True)
disease = gene.disease_list()[-1]
disease.set_chromosome(row[4])
position = int(row[5])
notes = row[9]
if 'Nucleotide # based on:' in notes:
type_pos = re.search(
r'Nucleotide # based on: ([^\s;]+)', notes).group(1)
elif position < 20000:
type_pos = "RELATIVE"
else:
type_pos = 'CHROMOSOME'
disease.set_position(position, type_pos)
disease.set_allele_change(row[6])
disease.set_amino_change(row[7])
# notes = row[9]
# if 'NM' in notes:
# allele_change = convert_to_chrom(allele_change)
print("Created tab file database complete")
def chart_binding_specifity(analysis='euclidean', create_spec=True):
"""
Creates a histogram displaying the change in binding specifity caused by
missense mutations in the DNA-binding region.
This function scans a list of PWM (obtained manually from zf.princeton.edu)
and outputs a charge that displays the euclidean distance of each mutation in
the DNA-binding region.
Parameter analysis: the method of analyzing
Preconditon: analysis is pearsons or Euclidean
Parameter create_spec: a boolean that says whether or not to create a new
chart
Preconditon: create_spec is a bool
"""
assert 'pearson' in analysis or 'euclidean' in analysis
filename_specifity = analysis + '.png'
filename = helper.edit_filename(filename_specifity,
"sibling",
foldername='output')
if not os.path.exists(filename) or create_spec:
# with open(filename, 'w+') as f:
# for ele in adict:
# f.write('%s\t%s\n' % (ele, adict[ele]))
if 'euclidean' in analysis:
xlabel = numpy.arange(0.0, 2.6, 0.2)
else:
xlabel = numpy.arange(0.0, 1.0, 0.05)
arr = count.quantify_dna_specifity(foldername='analysis',
analysis=analysis)
plt.hist(arr, color='lightgrey', ec='black', bins=xlabel)
plt.xticks(xlabel, fontsize=18)
plt.yticks(range(0, 10), fontsize=18)
plt.ylabel("Frequency", fontsize=24)
if 'euclidean' in analysis:
plt.xlabel("Euclidean Distance", fontsize=24)
else:
plt.xlabel("Pearson Correlation Coefficient", fontsize=24)
plt.title("Predicted Change in DNA Binding Specificity", fontsize=36)
figure = plt.gcf()
figure.set_size_inches(18, 9)
# plt.show() # Use this to see the chart.
plt.savefig(filename, format="png", dpi=100)
print(filename_specifity + " created successfully!")
def info_tab_diseased(alist,
filename_tab_dis="zf_genes_w_disease.tsv",
create_tab_dis=True):
"""
Creates a tab delimited file containing the disease information from a list
of genes with disease information
Parameter alist: the list to create the file from.
Precondtion: alist is a list
Parameter filename_tab:_dis a string to name the tab delimmited file ending in .txt
Preconditon: filename_tab_dis is a string ending in .txt
Parameter create_tab_dis: a boolean that says whether or not to create a new
tab delimited file.
Preconditon: create_tab_dis is a bool
"""
filename = helper.edit_filename(filename_tab_dis,
"sibling",
foldername='output')
if not os.path.exists(filename) or create_tab_dis:
with open(filename, "w+", encoding='utf-8') as g:
head = [
'Gene Name', 'Gene ID', 'Chromosome', 'Position of SNV',
'Allele Change', 'Amino Change', 'Disease Desc', 'SNP',
'Disease Source'
]
g.write('#' + '\t'.join(str(x) for x in head) + '\n')
for gene in alist:
disease_list = gene.disease_list()
for disease in disease_list:
if disease.has_full_info():
row = [
gene.get_gene_name(),
gene.get_gene_id(),
disease.get_chromosome(),
disease.get_string_full_position(),
disease.get_allele_change(),
disease.get_amino_change(),
disease.get_disease_name(),
disease.get_dbSNP(),
disease.get_source()
]
g.write('\t'.join(str(x) for x in row) + '\n')
print(filename_tab_dis + " created successfully!")
def info_chart(alist,
filename_chart="zf_protein_chart.png",
create_chart=True):
"""
Creates a chart visualizing the number of proteins that have a certain
number of domains.
Parameter alist: a list of genes
Precondtion: alist is a list of genes
Parameter filename_tab: a string to name the chart ending in png
Preconditon: filename_tab is a string ending in .png
Parameter create_chart: a boolean that says whether or not to create a chart
Preconditon: create_chart is a bool
"""
filename = helper.edit_filename(filename_chart,
"sibling",
foldername='output')
if not os.path.exists(filename) or create_chart:
dict_domains = count.dict_domains(alist)
left = []
height = []
for key in dict_domains:
left.append(key)
height.append(dict_domains[key])
tick_label = [str(i) for i in left]
plt.bar(left, height, tick_label=tick_label, width=0.4, color=["blue"])
plt.xlabel("Number of proteins")
plt.ylabel("Number of ZFs")
plt.title("Number of ZFs in ZF proteins")
figure = plt.gcf()
figure.set_size_inches(18, 9)
plt.rc('font', size=8)
# plt.show() #Use this to see the chart.
plt.savefig(filename, format="png", dpi=100)
print(filename_chart + " created successfully!")
def info_tab(alist, filename_tab="zf_protein_tabs.tsv", create_tab=True):
"""
Creates a tab delimited file containing the information from a list of genes.
Parameter alist: the list to create the file from.
Precondtion: alist is a list
Parameter filename_tab: a string to name the tab delimmited file ending in .txt
Preconditon: filename_tab is a string ending in .txt
Parameter create_tab: a boolean that says whether or not to create a new
tab delimited file.
Preconditon: create_tab is a bool
"""
filename = helper.edit_filename(filename_tab,
"sibling",
foldername='output')
if not os.path.exists(filename) or create_tab:
with open(filename, "w+", encoding='utf-8') as g:
head = [
'Gene Name', 'Gene ID', 'Protein ID', 'Core', 'Num Domains',
'Disease Info'
]
g.write('#' + '\t'.join(str(x) for x in head) + '\n')
for gene in alist:
protein_list = gene.protein_list()
for protein in protein_list:
row = [
gene.get_gene_name(),
gene.get_gene_id(),
protein.get_protein_id(),
protein.core_sequences(False),
protein.num_domains(),
gene.disease_str_without_full_info()
]
g.write('\t'.join(str(x) for x in row) + '\n')
print(filename_tab + " created successfully!")
def population_info(pop_list,
full_dict_proteins=dict(),
filename_pop="population_info.tsv",
create_pop=True):
"""
Outputs population info.
This function outputs a tab file for population information. This file can
then be searched through ExAC to get population information.
Parameter pop_list: a list of Genes
Preconditon: pop_list is a list of Genes
Parameter filename_pop: the name of the file
Preconditon: filename_pop is a string
Parameter create_pop: says whether to create a new file
Preconditon: create_pop is a boolean
"""
print("Creating population info file.")
if full_dict_proteins == dict():
full_dict_proteins = genetics.Protein.full_protein_dict(
"Homo_sapiens.GRCh37.pep.all.fa")
filename = helper.edit_filename(filename_pop,
"sibling",
foldername='output')
if not os.path.exists(filename) or create_pop:
with open(filename, "w+", encoding='utf-8') as g:
head = [
'Gene ID', 'Protein ID', 'Domain Number',
'Chromosome-Start_Pos-End_Pos', 'Core Indices',
'Ion-Binding Indices', 'Hydrophobic Indices'
]
g.write('#' + '\t'.join(str(x) for x in head) + '\n')
for gene in pop_list:
proteins = gene.protein_list()
for protein in proteins:
description = full_dict_proteins[protein.get_protein_id()]
match = re.search(r"GRCh37:(\w+):(\w+):(\w+)",
str(description))
try:
chromosome = match.group(1)
if len(chromosome) > 2:
int(X)
start_pos = match.group(2)
end_pos = match.group(3)
domains = protein.domain_list()
for domain in domains:
key_pos = domain.get_key_positions()
if len(key_pos) == 0:
pass
else:
g.write(gene.get_gene_id() + '\t')
g.write(protein.get_protein_id() + '\t')
g.write(str(domain.get_domain_number()) + '\t')
g.write(
str(chromosome) + '-' + str(start_pos) +
'-' + str(end_pos) + '\t')
g.write(str(key_pos['Core Indices']) + '\t')
g.write(
str(key_pos['Ion-Binding Indices']) + '\t')
g.write(str(key_pos['Hydrophobic Indices']))
g.write('\n')
except:
pass
print(filename_pop + " created successfully!")
def DNA_binding_list(DNA_list,
filename_DNA="DNA_binding_region_info.txt",
create_DNA=True):
"""
Parameter DNA_list: a list of genes.
Preconditon: DNA_list is a list of Genes.
Parameter filename_DNA: a string to name the info file ending in .txt
Preconditon: filename_DNA is a string ending in .txt
Parameter create_DNA: A boolean that says whether or not to create a new
text file.
Preconditon: create_DNA is a bool
"""
assert type(DNA_list) == list, "Gene list must be a list."
assert type(filename_DNA) == str, "Filename must be a string."
assert type(create_DNA) == bool, "Create mut must be a string."
print("Outputting DNA-binding region info")
file = helper.edit_filename(filename_DNA, "sibling", "output")
if not os.path.exists(file) or create_DNA:
today = date.today()
month = str(today.month)
day = str(today.day)
if len(month) < 2:
month = "0" + month
if len(day) < 2:
day = "0" + day
with open(file, 'w+', encoding='utf-8') as f:
f.write("This file was generated by the Python module " +
os.path.basename(__file__) + '\n\n')
f.write(
"This file contains information about missense mutations in the\n"
)
f.write(
"DNA-binding region. Specifically, this file gives information\n"
)
f.write(
"on the gene name, the protein ID, the domain number, the\n")
f.write("HMMER score, the disease information, as well as other\n")
f.write(
"relevant information about mutations in the DNA-binding region.\n\n"
)
f.write("Author: Austin Starks\nDate: " + month + "/" + day + "/" +
str(today.year) + '\n\n')
for gene in DNA_list:
proteins = gene.protein_list()
for protein in proteins:
domains = protein.domain_list()
for domain in sorted(domains):
mutation_dict = domain.get_mutation_dictionary()
ori_sequence = domain.domsequence()
if domain.is_valid:
for mut_seq in mutation_dict:
notes = mutation_dict[mut_seq][0]
disease = mutation_dict[mut_seq][4]
amino_change = mutation_dict[mut_seq][
4].get_amino_change()
allele_change = mutation_dict[mut_seq][
4].get_allele_change()
position = mutation_dict[mut_seq][
4].get_string_full_position()
Ter = amino_change[-3:]
if 'dna' in notes and Ter != 'Ter':
f.write("\nGene Name: " +
gene.get_gene_name() + '\n')
f.write("Protein ID: %s\n" %
protein.get_protein_id())
f.write("Domain number: " +
str(domain.get_domain_number()) +
' | ')
f.write("From " +
str(domain.get_start_position()) +
" to ")
f.write(
str(domain.get_end_position()) + '\n')
f.write("Score : " +
str(domain.get_score()) + '\n')
f.write("Original Sequence: " +
ori_sequence + '\n')
f.write("Mutated Sequence : " + mut_seq +
'\n')
f.write("Original Amino : " +
mutation_dict[mut_seq][1] + '\n')
f.write("Mutated Amino : " +
mutation_dict[mut_seq][2] + '\n')
f.write("Mutation Index : " +
str(mutation_dict[mut_seq][3]) +
'\n')
f.write("Amino Acid Change: " +
amino_change + '\n')
f.write("Allelic Change : " +
allele_change + '\n')
f.write("Allele Position : " + position +
'\n')
f.write("Disease Name : " +
disease.get_disease_name() + '\n')
f.write("Source : " +
disease.get_source() + '\n')
f.write("Sequence: \n%s\n\n" %
protein.prosequence())
f.write(
'\n-----------------------------------------------\n'
)
print(filename_DNA + " was created successfully!")
def info_mutation_list(mut_list,
filename_mut="mutation_list_info.txt",
create_mut=True):
"""
Parameter alist: a list of genes.
Preconditon: alist is a list of Genes.
Parameter filename_mut: a string to name the info file ending in .txt
Preconditon: filename_mut is a string ending in .txt
Parameter create_mut: A boolean that says whether or not to create a new
text file.
Preconditon: create_mut is a bool
"""
assert type(mut_list) == list, "Gene list must be a list."
assert type(filename_mut) == str, "Filename must be a string."
assert type(create_mut) == bool, "Create mut must be a string."
print("Gathering statistics about mutations.")
file = helper.edit_filename(filename_mut, "sibling", "output")
dna_count, ion_count, zf_muts = count.mutation_gene_stats(mut_list)
diseased_list = genetics.Gene.diseased_gene_list(print_=False)
initial = count.total_mutations(diseased_list)
total = count.total_mutations(mut_list)
stats_pro_dis = count.protein_and_disease_stats(mut_list)
missense = count.missense_mutation_stats(mut_list)
if not os.path.exists(file) or create_mut:
today = date.today()
month = str(today.month)
day = str(today.day)
if len(month) < 2:
month = "0" + month
if len(day) < 2:
day = "0" + day
with open(file, "w+", encoding='utf-8') as f:
f.write(
"This file was generated by the Python module " +
os.path.basename(__file__) + '\n\n' +
"This file contains information about the effects of\n" +
"mutations on human zinc finger proteins. Specifically,\n" +
"it lists the original and mutated zinc finger domains, and \n"
+
"describes if that mutation is on a zinc/dna-binding region.\n"
+ "This file also gives statistics about the region.\n\n"
"Author: Austin Starks\nDate: " + month + "/" + day + "/" +
str(today.year) + '\n\n')
f.write('\n----------------------------------------------\n\n')
f.write('Mutation Stats:\n')
f.write(
'The following are statistics about mutations in ZF domains.\n'
)
f.write(
'The diseases were "filtered" to remove mutations that were\n')
f.write('faulty.\n\nFor example:\nHis184Pro\n')
f.write(
"But when you check the 184th protein, it isn't Histidine.\n\n"
)
# f.write("Initial number of mutations : " +
# str(initial) + '\n')
f.write("# of mutations after filtering : " + str(total) +
'\n')
f.write("# of mutations in DNA-binding region : " +
str(dna_count) + '\n')
f.write("# of mutations in ion-binding region : " +
str(ion_count) + '\n')
f.write("# of mutations in zinc-finger domains : " +
str(zf_muts) + '\n')
f.write("# of missense mutations : %s\n" %
missense['Total missense mutations'])
f.write("# of nonsense mutations : %s\n" %
(missense['# of nonsense mutations']))
f.write(
"# of nonsense mut in section of 1 domain : %s\n" %
(missense[
'# of nonsense mutations eliminating a part of 1 domain']))
f.write(
"# of nonsense mut eliminating entire domain: %s\n" %
(missense[
'# of nonsense mutations eliminating an entire domain']))
f.write('\n----------------------------------------------\n')
f.write('\nProtein Stats:\n')
f.write(
'The following are statistics about the amino acids. Note the\n'
)
f.write(
'apparent overlap between these stats and the mutation stats.\n'
)
f.write(
"However, these stats are important for performing a Fisher's\n"
)
f.write("Exact test.\n\n")
for i in range(len(stats_pro_dis)):
tmp = stats_pro_dis[i]
for j in tmp:
msg = j
while len(msg) < 52:
msg += ' '
f.write(msg + ': ' + str(tmp[j]) + '\n')
f.write('\n----------------------------------------------\n')
f.write("\nMissense Stats:\n")
f.write(
"The following are statistics about missense mutations. These\n"
)
f.write(
"stats are used to get information on the number of missense\n"
)
f.write(
"mutations (point mutations that don't end with termination of\n"
)
f.write("the protein transcript).\n\n")
for ele in missense:
msg = ele
while len(msg) < 40:
msg += ' '
f.write(msg + ": " + str(missense[ele]) + '\n')
f.write('\n----------------------------------------------\n')
for gene in mut_list:
proteins = gene.protein_list()
f.write("\nGene Name: " + gene.get_gene_name() + '\n')
f.write("Gene ID: " + gene.get_gene_id() + '\n')
f.write("Chromosome: %s" %
gene.disease_list()[0].get_chromosome() + '\n')
for protein in proteins:
f.write("Protein ID: " + protein.get_protein_id() + '\n')
domains = protein.domain_list()
for domain in sorted(domains):
mutation_dict = domain.get_mutation_dictionary()
ori_sequence = domain.domsequence()
f.write("\n---\nDomain number: " +
str(domain.get_domain_number()) + ' | ')
f.write("From " + str(domain.get_start_position()) +
" to ")
f.write(str(domain.get_end_position()) + '\n')
f.write("Score : " +
str(domain.get_score()) + '\n')
if domain.is_valid():
f.write("Original Sequence: " + ori_sequence +
'\n\n')
for mut_seq in mutation_dict:
notes = mutation_dict[mut_seq][0]
disease = mutation_dict[mut_seq][4]
if notes != "none":
notes = notes + " region"
f.write("Mutated Sequence : " + mut_seq + '\n')
f.write("Original Amino : " +
mutation_dict[mut_seq][1] + '\n')
f.write("Mutated Amino : " +
mutation_dict[mut_seq][2] + '\n')
f.write("Mutation Index : " +
str(mutation_dict[mut_seq][3]) + '\n')
f.write("Amino Acid Change: " +
mutation_dict[mut_seq]
[4].get_amino_change() + '\n')
f.write("Allelic Change : " +
mutation_dict[mut_seq]
[4].get_allele_change() + '\n')
f.write("Allele Position : %s\n" %
mutation_dict[mut_seq]
[4].get_string_full_position())
f.write("Disease Name : " +
disease.get_disease_name() + '\n')
f.write("Source : " +
disease.get_source() + '\n')
f.write("Notes : " + notes + '\n')
f.write('\n')
else:
f.write("Invalid C2H2 ZF Domain\n\n")
f.write('\n----------------------------------------------\n\n')
f.write('\n\n----------------------------------------------\n\n')
f.write(
"The following diseases did not affect a zinc finger domain:\n"
)
for gene in mut_list:
diseases = gene.disease_list()
for disease in diseases:
if not disease.get_hit_domain():
f.write("Gene name: " + gene.get_gene_name() + ' | ')
f.write("Gene ID: " + gene.get_gene_id() + '\n')
f.write("Disease: " + disease.get_disease_name() +
'\n')
f.write("Allelic position: " +
disease.get_string_full_position() + ' | ')
f.write("Allelic substitution: " +
disease.get_allele_change() + ' | ')
f.write("Chromosome: " +
str(disease.get_chromosome()) + '\n')
f.write("Amino acid substitution: " +
disease.get_amino_change() + ' | ')
f.write("Source: " + disease.get_source() + '\n')
f.write('\n')
f.write('\n----------------------------------------------\n')
print(filename_mut + " was created successfully!")
def removed_disease_list(gene_list,
removal,
filename="removed_disease_info.txt",
create_dis_list=False):
"""
Outputs info about removed diseases.
This procedure outputs information about diseases that are to be removed.
Information includes the protein
Parameter gene_list: a list of genes.
Preconditon: gene_list is a list of Genes.
Parameter removal: a set of diseases to remove
Preconditon removal is a set of Diseases
Parameter filename: a string to name the info file ending in .txt
Preconditon: filename_txt is a string ending in .txt
Parameter create_dis_list: A boolean that says whether or not to create a new
text file.
Preconditon: create_dis_list is a bool
"""
assert type(gene_list) == list, "Gene list must be a list."
assert type(removal) == dict, "Removal must be a dict of diseases."
assert type(filename) == str, "Filename must be a string."
file = helper.edit_filename(filename, "sibling", "output")
if not os.path.exists(file) or create_dis_list:
today = date.today()
month = str(today.month)
day = str(today.day)
abool = False
if len(month) < 2:
month = "0" + month
if len(day) < 2:
day = "0" + day
with open(file, "w+", encoding='utf-8') as f:
f.write(
"This file was generated by the Python module " +
os.path.basename(__file__) + '\n\n' +
"This file contains information about the diseases that\n" +
"were removed from the disease list. Specifically, this\n" +
"file outputs the gene associated with the disease,\n" +
"the list of proteins that the gene codes for, the allelic\n" +
"and amino acid substitution, the position of the mutation,\n"
+ "and other important info.\n\n" +
"Author: Austin Starks\nDate: " + month + "/" + day + "/" +
str(today.year) + '\n\n')
f.write("Number of diseases removed: " + str(len(removal)))
f.write('\n----------------------------------------------\n\n')
for gene in gene_list:
diseases = gene.disease_list()
for disease in diseases:
if disease in removal:
abool = True
f.write('\nGene name: ' + gene.get_gene_name() +
'\nGene ID:' + gene.get_gene_id() + '\n')
f.write('Disease description: ' +
disease.get_disease_name() + '\n')
f.write('Disease source: ' + disease.get_source() +
'\n')
f.write('Disease allelic position: ' +
disease.get_string_full_position() + '\n')
f.write('Disease allelic change: ' +
disease.get_allele_change() + '\n')
f.write('Disease amino change: ' +
disease.get_amino_change() + '\n')
f.write('Notes: ' + removal[disease] + '\n')
if abool:
abool = False
proteins = gene.protein_list()
for protein in proteins:
f.write('\nProtein ID: ' + protein.get_protein_id() +
'\n\n')
f.write('Protein Seq:\n' + str(protein.prosequence()) +
'\n')
f.write(
'\n----------------------------------------------\n')
if create_dis_list:
print("Text file about removed diseases created successfully.")
else:
print("Text file about removed diseases is already there. \n Change" +
" create_dis_list to be True.")
def info_txt(alist, filename_txt="zf_protein_info.txt", create_txt=True):
"""
Creates a text file containing the information from a list of genes.
Parameter alist: the list to create the file from.
Precondtion: alist is a list
Parameter full_dict: a dictionary of the full list of proteins. Used by
statistics to gather information about the proteins
Preconditon: full_dict is a dictionary of protein IDs
Parameter filename_txt: a string to name the info file ending in .txt
Preconditon: filename_txt is a string ending in .txt
Parameter create_txt: A boolean that says whether or not to create a new
text file.
Preconditon: create_txt is a bool
"""
filename = helper.edit_filename(filename_txt,
"sibling",
foldername='output')
if not os.path.exists(filename) or create_txt:
full_dict = genetics.Protein.full_protein_dict()
x = Texttable()
today = date.today()
month = str(today.month)
day = str(today.day)
if len(month) < 2:
month = "0" + month
if len(day) < 2:
day = "0" + day
with open(filename, "w+", encoding='utf-8') as f:
stats = count.zf_protein_stats(alist, full_dict)
f.write(
"This text file was generated by the Python module " +
os.path.basename(__file__) + "." + "\n\n" +
"This file contains information " +
"about genes, including their \ngene IDs, their common names, and the list of "
+
"proteins they \ncode for. This file also contains information about the \n"
+
"proteins including the number of ZF domains in each protein, \ntheir core "
+ "sequences, and statistics about the proteins." +
"\n\nAuthor: Austin Starks\nDate: " + month + "/" + day + "/" +
str(today.year))
f.write(stats + "Gene info: \n\nNote: A core sequence of '????' " +
"indicates that domain is likely invalid.\n\n")
categories = [
"Gene name", "Protein ID", "Core Seqs", "# ZFs", "Diseases"
]
x.add_row(categories)
for gene in alist:
protein_list = gene.protein_list()
for protein in protein_list:
row = [
gene.get_gene_name(),
protein.get_protein_id(),
protein.core_sequences(),
protein.num_domains(),
gene.disease_list_string()
]
x.add_row(row)
f.write(x.draw())
print(filename_txt + " created successfully!")
