def make_igv(url, files_dir):
# Get all file types in files_dir.
file_list = list(
set(os.path.splitext(file)[1] for file in os.listdir(files_dir)))
ext_list = [x for x in file_list if x in FILE_EXTENSIONS]
# Get track types
track_types = list(map(lambda item: item.replace(".", ""), ext_list))
# Get the genome file.
fasta_idx = os.path.join(files_dir, f'*.fa.fai')
genome = glob.glob(fasta_idx)[0].replace(".fai", "")
genome = os.path.basename(genome)
# Collect all bam files.
bam_files = get_files(files_dir, f'*.bam')
# Collect all samples.
samples = [os.path.splitext(os.path.basename(f))[0] for f in bam_files]
path = os.path.join(url, os.path.basename(files_dir))
# Render template.
igv_template = "igv.xml"
data = dict(genome=genome,
path=path,
samples=samples,
track_types=track_types)
html = render_template(data, igv_template)
print(html)
def demo():
from random import randint
def make(x):
value = randint(1, 5)
return f'A{value}', value
p1 = ChartParams()
p1.data = map(make, range(50))
p1.xlabel = "Size 1"
p1.ylabel = "Value 1"
p1.options = '''
title: 'Histogram Plot 1',
legend: {position: 'none'},
'''
p2 = ChartParams()
p2.type = 'BarChart'
p2.data = map(make, range(15))
p2.xlabel = "Size 2"
p2.ylabel = "Value 2"
p2.options = '''
title: 'Histogram Plot 2' ,
legend: {position: 'none'},
'''
# Plot table.
t1 = TableParams()
rows = [["'Mike'", 10000, 'true'], ["'Jim'", 8000, 'false'],
["'Alice'", 12500, 'true'], ["'Bob'", 7000, 'false']]
columns = [('string', 'Name'), ('number', 'Salary'),
('boolean', 'Full Time Employee')]
t1.columns = columns
t1.rows = rows
t1.options = '''
title: 'Table 1',
width: '50%',
height: '50%'
'''
# This is the context.
data = dict(p1=p1, p2=p2, t1=t1)
name = "chart_demo.html"
html = render_template(data, name)
with open('index.html', 'wt') as fp:
fp.write(html)
def plot(data1, data2, data3):
# Plot 1
# Sort by counts.
data1.sort(key=lambda x: int(x[1]), reverse=True)
# Get only single-end specific details.
details = [
'total', 'mapped', 'supplementary', 'secondary', 'duplicates',
'singletons'
]
data1 = list(filter(lambda x: x[0].lower() in details, data1))
p1 = ChartParams()
p1.type = 'BarChart'
p1.data = data1
p1.xlabel = "Flag category"
p1.ylabel = "Read counts"
p1.options = '''
title: '',
legend: {position: 'none'},
colors : ['green']
'''
# Plot 2
p2 = ChartParams()
p2.type = 'BarChart'
p2.data = data2
p2.xlabel = "Chromosomes"
p2.ylabel = "Read counts"
p2.options = '''
title: '',
legend: {position: 'none'},
colors: ['green']
'''
# Plot table.
t1 = TableParams()
t1.rows = data3.rows
t1.columns = data3.columns
t1.options = '''
width : '100%',
height : '50%'
'''
# This is the context.
data = dict(p1=p1, p2=p2, t1=t1)
name = "bwa_classify.html"
html = render_template(data, name)
print(html)
def plot(data):
# Plot 1
p1 = ChartParams()
p1.type = 'BarChart'
p1.data = data
p1.xlabel = "Species"
p1.ylabel = "Read counts"
p1.options = '''
title: 'Unique reads in species',
legend: {position: 'none'},
'''
# Plot 2
p2 = ChartParams()
p2.type = 'PieChart'
p2.data = data
p2.xlabel = "Species"
p2.ylabel = "Read counts"
p2.options = '''
title: 'Unique reads in species',
chartArea:{left:20,top:0,width:'80%',height:'75%'},
legend:{position:'left'}
'''
# Plot3
locations = [(41.015908, -77.53246, 'Lamar PA')]
p3 = ChartParams()
p3.type = 'Map'
p3.data = locations
p3.options = '''
zoomLevel: 6,
showTooltip: true,
showInfoWindow: true
'''
# This is the context.
data = dict(p1=p1, p2=p2, p3=p3)
name = "classify.html"
html = render_template(data, name)
print(html)
def plot(data1, data2):
# Plot 1
# Sort by counts.
data1.sort(key=lambda x: int(x[1]), reverse=True)
# Get only single-end specific details.
details = [
'total', 'mapped', 'supplementary', 'secondary', 'duplicates',
'singletons'
]
data1 = list(filter(lambda x: x[0].lower() in details, data1))
p1 = ChartParams()
p1.type = 'BarChart'
p1.data = data1
p1.xlabel = "Flag category"
p1.ylabel = "Read counts"
p1.options = '''
title: 'Alignment details.',
legend: {position: 'none'},
'''
# Plot 2
p2 = ChartParams()
p2.type = 'BarChart'
p2.data = data2
p2.xlabel = "Chromosomes"
p2.ylabel = "Read counts"
p2.options = '''
title: 'Mapped counts per chromosome.',
legend: {position: 'none'},
'''
# This is the context.
data = dict(p1=p1, p2=p2)
name = "align/align_index.html"
html = render_template(data, name)
print(html)
return plot1
if __name__ == '__main__':
import argparse
parser = argparse.ArgumentParser(
description='Create barcharts from samtools idxstats output.')
parser.add_argument('--mapped', help='File with idxstats output ')
parser.add_argument('--total', help='File with total read counts ')
parser.add_argument('--selected',
help='No. of reads subselected for mapping')
args = parser.parse_args()
# Read the arguments
mapped = args.mapped
total = args.total
selected = args.selected
plot1 = create_plot(mapped, total, selected)
# This is the context.
data = dict(p1=plot1)
name = "align/scaffold_index.html"
html = render_template(data, name)
print(html)