def add_known(x_L, x_R, y_L, y_R, gap, genbank, ref, seq, temp, cds, trna, rrna, region, feature_count, results, features, feature_list, removed_results, line, file_loc):
'''
Adds a value to the table that is a known hit
'''
# Get orientation
if y_L < x_R:
start = y_L
end = x_R
orient = 'F'
else:
start = y_R
end = x_L
orient = 'R'
# Get features and append to genbank
note = 'Known hit'
left_feature, right_feature = createFeature([x_L, y_L, x_R, y_R], orient, note)
genbank.features.append(left_feature)
genbank.features.append(right_feature)
# Check to see if the sequence between actually belongs to the IS query
seq_results = check_seq_between(ref, seq, start, end, 'region_' + str(region), temp)
# This is a known site of coverage and %ID above 80
if len(seq_results) != 0 and seq_results[0] >= 80 and seq_results[1] >= 80:
# Taking all four coordinates and finding min and max to avoid coordinates
# that overlap the actual IS (don't want to return those in gene calls)
# Mark as a known call to improve accuracy of gene calling
gene_left, gene_right = get_flanking_genes(features, feature_list, start, end, cds, trna, rrna)
#gene_left = get_other_gene(ref, min(y_L, y_R, x_R, x_L), "left", cds, trna, rrna, known=True)
#gene_right = get_other_gene(ref, max(y_L, y_R, x_R, x_L), "right", cds, trna, rrna, known=True)
# If the genes are the same, then this gene must be interrupted by the known site
if gene_left[0] == gene_right[0]:
func_pred = 'Gene interrupted'
# Remove + and - from distance as the gene is interrupted
gene_right[1] = gene_right[1][:-1]
gene_left[1] = gene_left[1][:-1]
# Otherwise we need to determine who is upstream/downstream of what
else:
func_pred = ''
func_pred = ''
# Add to the final results
if 'unpaired' in file_loc:
call = 'Known?'
else:
call = 'Known'
results['region_' + str(region)] = [orient, str(start), str(end), gap, call, str(seq_results[0]), str('%.2f' % seq_results[1]), gene_left[-1][:-1], gene_left[-1][-1], gene_left[1], gene_right[-1][:-1], gene_right[-1][-1], gene_right[1], func_pred]
else:
# Then I'm not sure what this is
# Get flanking genes anyway
gene_left, gene_right = get_flanking_genes(features, feature_list, start, end, cds, trna, rrna)
if 'unpaired' in file_loc:
call = 'Possible related IS?'
else:
call = 'Possible releated IS'
func_pred = ''
if len(seq_results) !=0:
results['region_' + str(region)] = [orient, str(start), str(end), gap, call, str(seq_results[0]), str('%.2f' % seq_results[1]), gene_left[-1][:-1], gene_left[-1][-1], gene_left[1], gene_right[-1][:-1], gene_right[-1][-1], gene_right[1], func_pred]
else:
removed_results['region_' + str(region)] = line.strip() + '\t' + file_loc +'\n'
def novel_hit(x_L, y_L, x_R, y_R, x, y, genbank, ref, cds, trna, rrna, gap, orient, feature_count, region, results, features, feature_list, unpaired=False, star=False):
'''
Get flanking gene information for novel hits.
'''
# Create features for genbank
note = 'Novel hit'
if unpaired == True:
note += ' , unpaired hit'
if star == True:
note += ' , imprecise hit'
left_feature, right_feature = createFeature([x_L, y_L, x_R, y_R], orient, note)
# Add features to genbank
genbank.features.append(left_feature)
genbank.features.append(right_feature)
# Get the genes flanking the left and right ends
gene_left, gene_right = get_flanking_genes(features, feature_list, x, y, cds, trna, rrna)
#print gene_left
#print gene_right
# If the genes are the same, then hit is inside the gene
if gene_left[-1] == gene_right[-1]:
func_pred = 'Gene interrupted'
else:
func_pred = ''
func_pred = ''
# This is a confident hit
if unpaired == False:
call = 'Novel'
# Hit is paired with a low coverage end, so an unconfident hit
elif unpaired == True:
call = 'Novel?'
# This hit is imprecise, as gap size is larger than expected
if star == True:
call = 'Novel*'
# Store all information for final table output
results['region_' + str(region)] = [orient, str(x), str(y), gap, call, '', '', gene_left[-1][:-1], gene_left[-1][-1], gene_left[1], gene_right[-1][:-1], gene_right[-1][-1], gene_right[1], func_pred]
def add_known(x_L, x_R, y_L, y_R, gap, genbank, ref, seq, temp, cds, trna,
rrna, region, feature_count, results, features, feature_list,
removed_results, line, file_loc):
'''
Adds a value to the table that is a known hit
'''
# Get orientation
if y_L < x_R:
start = y_L
end = x_R
orient = 'F'
else:
start = y_R
end = x_L
orient = 'R'
# Get features and append to genbank
note = 'Known hit'
left_feature, right_feature = createFeature([x_L, y_L, x_R, y_R], orient,
note)
genbank.features.append(left_feature)
genbank.features.append(right_feature)
# Check to see if the sequence between actually belongs to the IS query
seq_results = check_seq_between(ref, seq, start, end,
'region_' + str(region), temp)
# This is a known site of coverage and %ID above 80
if len(seq_results) != 0 and seq_results[0] >= 80 and seq_results[1] >= 80:
# Taking all four coordinates and finding min and max to avoid coordinates
# that overlap the actual IS (don't want to return those in gene calls)
# Mark as a known call to improve accuracy of gene calling
gene_left, gene_right = get_flanking_genes(features, feature_list,
start, end, cds, trna, rrna)
#gene_left = get_other_gene(ref, min(y_L, y_R, x_R, x_L), "left", cds, trna, rrna, known=True)
#gene_right = get_other_gene(ref, max(y_L, y_R, x_R, x_L), "right", cds, trna, rrna, known=True)
# If the genes are the same, then this gene must be interrupted by the known site
if gene_left[0] == gene_right[0]:
func_pred = 'Gene interrupted'
# Remove + and - from distance as the gene is interrupted
gene_right[1] = gene_right[1][:-1]
gene_left[1] = gene_left[1][:-1]
# Otherwise we need to determine who is upstream/downstream of what
else:
func_pred = ''
func_pred = ''
# Add to the final results
if 'unpaired' in file_loc:
call = 'Known?'
else:
call = 'Known'
results['region_' + str(region)] = [
orient,
str(start),
str(end), gap, call,
str(seq_results[0]),
str('%.2f' % seq_results[1]), gene_left[-1][:-1],
gene_left[-1][-1], gene_left[1], gene_right[-1][:-1],
gene_right[-1][-1], gene_right[1], func_pred
]
else:
# Then I'm not sure what this is
# Get flanking genes anyway
gene_left, gene_right = get_flanking_genes(features, feature_list,
start, end, cds, trna, rrna)
if 'unpaired' in file_loc:
call = 'Possible related IS?'
else:
call = 'Possible releated IS'
func_pred = ''
if len(seq_results) != 0:
results['region_' + str(region)] = [
orient,
str(start),
str(end), gap, call,
str(seq_results[0]),
str('%.2f' % seq_results[1]), gene_left[-1][:-1],
gene_left[-1][-1], gene_left[1], gene_right[-1][:-1],
gene_right[-1][-1], gene_right[1], func_pred
]
else:
removed_results[
'region_' +
str(region)] = line.strip() + '\t' + file_loc + '\n'
def novel_hit(x_L,
y_L,
x_R,
y_R,
x,
y,
genbank,
ref,
cds,
trna,
rrna,
gap,
orient,
feature_count,
region,
results,
features,
feature_list,
unpaired=False,
star=False):
'''
Get flanking gene information for novel hits.
'''
# Create features for genbank
note = 'Novel hit'
if unpaired == True:
note += ' , unpaired hit'
if star == True:
note += ' , imprecise hit'
left_feature, right_feature = createFeature([x_L, y_L, x_R, y_R], orient,
note)
# Add features to genbank
genbank.features.append(left_feature)
genbank.features.append(right_feature)
# Get the genes flanking the left and right ends
gene_left, gene_right = get_flanking_genes(features, feature_list, x, y,
cds, trna, rrna)
#print gene_left
#print gene_right
# If the genes are the same, then hit is inside the gene
if gene_left[-1] == gene_right[-1]:
func_pred = 'Gene interrupted'
else:
func_pred = ''
func_pred = ''
# This is a confident hit
if unpaired == False:
call = 'Novel'
# Hit is paired with a low coverage end, so an unconfident hit
elif unpaired == True:
call = 'Novel?'
# This hit is imprecise, as gap size is larger than expected
if star == True:
call = 'Novel*'
# Store all information for final table output
results['region_' + str(region)] = [
orient,
str(x),
str(y), gap, call, '', '', gene_left[-1][:-1], gene_left[-1][-1],
gene_left[1], gene_right[-1][:-1], gene_right[-1][-1], gene_right[1],
func_pred
]