def __init__(self, chromosome, strand, abundance, mappings, positions):
"""Create read object. Invoke with a constructor rather than directly.
Keyword Arguments:
chromosome -- reference sequence name, often a chromosome
strand -- read strand relative to the reference ['+'|'-'|'.']
abundance -- identical reads represented by the same alignment
mappings -- alignment positions for this read
positions -- array of 1-based chromosome positions the read covers """
self.chromosome = chromosome
if strand != "+" and strand != "-":
self.strand = "."
else:
self.strand = strand
if self.strand == "-":
positions.reverse()
self.position_array = positions
if confirm_integer(abundance, "Abundance", minimum=1):
self.abundance = int(abundance)
if mappings == "Unknown":
self.mappings = 1
elif confirm_integer(mappings, "Alignments", minimum=1):
self.mappings = int(mappings)
def __init__(self, chromosome, strand, abundance, mappings, positions):
"""Create read object. Invoke with a constructor rather than directly.
Keyword Arguments:
chromosome -- reference sequence name, often a chromosome
strand -- read strand relative to the reference ['+'|'-'|'.']
abundance -- identical reads represented by the same alignment
mappings -- alignment positions for this read
positions -- array of 1-based chromosome positions the read covers """
self.chromosome = chromosome
if strand != "+" and strand != "-":
self.strand = "."
else:
self.strand = strand
if self.strand == "-":
positions.reverse()
self.position_array = positions
if confirm_integer(abundance, "Abundance", minimum=1):
self.abundance = int(abundance)
if mappings == "Unknown":
self.mappings = 1
elif confirm_integer(mappings, "Alignments", minimum=1):
self.mappings = int(mappings)
def __init__(self, interval=1, padding_upstream=0, padding_downstream=0):
"""Return metagene instance defined by interval and padding sizes.
Keyword arguments:
interval -- length of interval (default 1)
padding_upstream -- length of upstream padding (default 0)
padding_downstream -- length of downstream padding (default 0)
"""
if confirm_integer(interval, "Interval", minimum=1):
self.feature_interval = int(interval)
self.padding = {'Upstream': None, 'Downstream': None}
if confirm_integer(padding_upstream, "Upstream padding", minimum=0):
self.padding['Upstream'] = int(padding_upstream)
if confirm_integer(padding_downstream, "Downstream padding",
minimum=0):
self.padding['Downstream'] = int(padding_downstream)
self.length = (self.padding['Upstream'] + self.feature_interval +
self.padding['Downstream'])
def __init__(self, interval=1, padding_upstream=0, padding_downstream=0):
"""Return metagene instance defined by interval and padding sizes.
Keyword arguments:
interval -- length of interval (default 1)
padding_upstream -- length of upstream padding (default 0)
padding_downstream -- length of downstream padding (default 0)
"""
if confirm_integer(interval, "Interval", minimum=1):
self.feature_interval = int(interval)
self.padding = {'Upstream': None, 'Downstream': None}
if confirm_integer(padding_upstream, "Upstream padding", minimum=0):
self.padding['Upstream'] = int(padding_upstream)
if confirm_integer(padding_downstream, "Downstream padding", minimum=0):
self.padding['Downstream'] = int(padding_downstream)
self.length = (self.padding['Upstream'] +
self.feature_interval +
self.padding['Downstream'])
def __init__(self,
count_method,
metagene_object,
name,
chromosome,
start,
end,
strand,
gap_counting=False,
ignore_strand=False):
"""Not normally called directly; use Feature.create(file_format, count_method,
metagene_object, feature_line, chromosome_conversion_table) to call indirectly.
Define a new feature with an interval (represents feature length),
up and downstream padding (defined by metagene_object), and genomic
(1-based) start and end positions.
Once defined here, the start and end represent the true start and end of
the feature. Therefore, if a - strand (Crick strand) feature the start
will be larger than the end.
"""
chromosome = Feature.chromosome_conversion[
chromosome] # convert to BAM-like chromosome designation
if (confirm_integer(start,
"Start",
minimum=1,
maximum=Read.chromosome_sizes[chromosome]) and
confirm_integer(end,
"End",
minimum=1,
maximum=Read.chromosome_sizes[chromosome])):
start = int(start)
end = int(end)
# Define feature-specific metagene where feature_interval respresents
# the length of the feature NOT the length of the final metagene interval
if count_method == 'all':
interval = (end - start + 1) # length of feature
else:
interval = 1 # length of the start (or end) of feature
Metagene.__init__(self, interval, metagene_object.padding['Upstream'],
metagene_object.padding['Downstream'])
self.name = name
self.chromosome = chromosome
self.strand = strand
self.metagene_length = metagene_object.feature_interval
# define counts_array dictionary
# key: orientation:gap_counts string
# where orientation = {'unstranded', 'sense', 'antisense'}
# gap_counts = {'ungapped', 'gapped, 'allreads'}
# 'ungapped' + 'gapped' = 'allreads'
# 'sense' + 'antisense' = 'unstranded'
#
# values: arrays of self.length initialized to 0
if self.strand != "+" and self.strand != "-":
self.strand = "."
orientation = ['unstranded']
elif ignore_strand:
orientation = ['unstranded']
else:
orientation = ['sense', 'antisense']
if gap_counting:
gap_counts = ['ungapped', 'gapped']
else:
gap_counts = ['allreads']
self.counts_array = {}
for o in orientation:
for g in gap_counts:
self.counts_array["{}:{}".format(o, g)] = []
for p in range(self.length):
#self.counts_array["{}:{}".format(o,g)].append(decimal.Decimal(0.0))
self.counts_array["{}:{}".format(o, g)].append(0)
# define position_array
# values : chromosomal 1-based nucleotide positions in 5' to 3'
# orientation WITH RESPECT TO THE FEATURE
# Example :
# + strand: [10,11,12,13,14,15]
# - strand: [15,14,13,12,11,10]
# so position_array[0] is always the start of the feature (with upstream padding)
# position_array[-1] is always the end of the feature (with downstream padding)
self.position_array = []
if self.strand == "-":
# chromosome start = feature end
# chromosome end = feature start
if count_method == 'start':
start = end
elif count_method == 'end':
end = start
region_start = start - self.padding[
'Downstream'] # start is really end
region_end = end + self.padding['Upstream'] # end is really start
positions = range(region_start, region_end + 1) # inclusive list
positions.reverse()
else:
if count_method == 'start':
end = start # set both start and end to the start value
elif count_method == 'end':
start = end # set both start and end to the end value
region_start = start - self.padding['Upstream']
region_end = end + self.padding['Downstream']
positions = range(region_start, region_end + 1) # inclusive list
self.position_array = positions
def __init__(
self,
count_method,
metagene_object,
name,
chromosome,
start,
end,
strand,
gap_counting=False,
ignore_strand=False,
):
"""Not normally called directly; use Feature.create(file_format, count_method,
metagene_object, feature_line, chromosome_conversion_table) to call indirectly.
Define a new feature with an interval (represents feature length),
up and downstream padding (defined by metagene_object), and genomic
(1-based) start and end positions.
Once defined here, the start and end represent the true start and end of
the feature. Therefore, if a - strand (Crick strand) feature the start
will be larger than the end.
"""
chromosome = Feature.chromosome_conversion[chromosome] # convert to BAM-like chromosome designation
if confirm_integer(start, "Start", minimum=1, maximum=Read.chromosome_sizes[chromosome]) and confirm_integer(
end, "End", minimum=1, maximum=Read.chromosome_sizes[chromosome]
):
start = int(start)
end = int(end)
# Define feature-specific metagene where feature_interval respresents
# the length of the feature NOT the length of the final metagene interval
if count_method == "all":
interval = end - start + 1 # length of feature
else:
interval = 1 # length of the start (or end) of feature
Metagene.__init__(self, interval, metagene_object.padding["Upstream"], metagene_object.padding["Downstream"])
self.name = name
self.chromosome = chromosome
self.strand = strand
self.metagene_length = metagene_object.feature_interval
# define counts_array dictionary
# key: orientation:gap_counts string
# where orientation = {'unstranded', 'sense', 'antisense'}
# gap_counts = {'ungapped', 'gapped, 'allreads'}
# 'ungapped' + 'gapped' = 'allreads'
# 'sense' + 'antisense' = 'unstranded'
#
# values: arrays of self.length initialized to 0
if self.strand != "+" and self.strand != "-":
self.strand = "."
orientation = ["unstranded"]
elif ignore_strand:
orientation = ["unstranded"]
else:
orientation = ["sense", "antisense"]
if gap_counting:
gap_counts = ["ungapped", "gapped"]
else:
gap_counts = ["allreads"]
self.counts_array = {}
for o in orientation:
for g in gap_counts:
self.counts_array["{}:{}".format(o, g)] = []
for p in range(self.length):
# self.counts_array["{}:{}".format(o,g)].append(decimal.Decimal(0.0))
self.counts_array["{}:{}".format(o, g)].append(0)
# define position_array
# values : chromosomal 1-based nucleotide positions in 5' to 3'
# orientation WITH RESPECT TO THE FEATURE
# Example :
# + strand: [10,11,12,13,14,15]
# - strand: [15,14,13,12,11,10]
# so position_array[0] is always the start of the feature (with upstream padding)
# position_array[-1] is always the end of the feature (with downstream padding)
self.position_array = []
if self.strand == "-":
# chromosome start = feature end
# chromosome end = feature start
if count_method == "start":
start = end
elif count_method == "end":
end = start
region_start = start - self.padding["Downstream"] # start is really end
region_end = end + self.padding["Upstream"] # end is really start
positions = range(region_start, region_end + 1) # inclusive list
positions.reverse()
else:
if count_method == "start":
end = start # set both start and end to the start value
elif count_method == "end":
start = end # set both start and end to the end value
region_start = start - self.padding["Upstream"]
region_end = end + self.padding["Downstream"]
positions = range(region_start, region_end + 1) # inclusive list
self.position_array = positions
