def convert_tojs(input_file, output_file, positions, config):
'''
Convert the input files to Json data and write them to the Javascript file
Also write functions and methods to process those data
Parameters
----------
input_file : str : The absolute path of formatted data file
output_file: str : The absolute path of JavaScript file
positions : dict: A nested dictionary with "must" and "option" as keys
config : configparser.RawConfigParser
Return
------
On success, return a dictionary: {"id_list": [...] "group_list": [...], "color": [...]}
id_list : The values for id column
group_list: The names of groups
color : The colors in groups
'''
import paplot.subcode.data_frame as data_frame
import paplot.subcode.merge as merge
import paplot.subcode.tools as tools
import paplot.convert as convert
import os
import math
# genome_size: a nested list
# [ [ A chromosome number in lowercase letters,
# The size of the 1st element,
# The color of the 1st element,
# The original name of the 1st element(that is not necessarily lowercase) or a user-defined name, ], ... ]
genome_size = load_genome_size(config)
if len(genome_size) == 0:
return None
# genome: dictionary-style string like this
# {"chr":"00", "size":249250621, "color":"#BBBBBB", "label":"1",},
# {"chr":"01", "size":243199373, "color":"#BBBBBB", "label":"2",},
# ...
# chr : Sequential number
# size : Size corresponding to the label
# color: Color corresponding to the label
# label: Name corresponding to chromosome
genome = ""
for i in range(len(genome_size)):
if len(genome) > 0:
genome += ",\n"
genome += genome_size_template.format(Chr=i, size=genome_size[i][1], color=genome_size[i][2], label=genome_size[i][3])
# Create a data frame that has title and data attributions
# title is a list like ['Break1', 'Break2', 'Chr1', 'Chr2', 'Sample']
# data is a nested list like [[16019088, 62784483, '14', '12', 'SAMPLE1'], ...]
try:
df = data_frame.load_file(
input_file, header=1,
sept=tools.config_getstr(config, "result_format_ca", "sept"),
comment=tools.config_getstr(config, "result_format_ca", "comment")
)
except Exception as e:
print("failure open data %s, %s" % (input_file, e.message))
return None
if len(df.data) == 0:
print("no data %s" % input_file)
return None
# Create groups, labels, and colors_n
# cols_di: a dictionary that merges must and option values
# : ex) {'chr1': 'Chr1', 'break1': 'Break1', 'chr2': 'Chr2', 'break2': 'Break2', 'id': 'Sample'}
cols_di = merge.position_to_dict(positions)
if "group" in cols_di:
for i in range(len(df.data)):
# A title may be stored in cols_di["group"]
group_pos = df.name_to_index(cols_di["group"]) # Get group(title) index
group = df.data[i][group_pos] # Get group(title) value for row i
# Modify group value
df.data[i][group_pos] = group.replace(" ", "_")
if group == "":
df.data[i][group_pos] = "_blank_"
# groups : list: group names
# labels : list: group names
# colors_n: list: color values for groups
[groups, colors_n] = convert.group_list(df.column(cols_di["group"]), "ca", "group", config)
labels = groups
else:
groups = ["outer", "inner"]
labels = ["Inter-chromosome", "Intra-chromosome"]
colors_n = ["#9E4A98", "#51BF69"] # purple, green
# Create group_text that is a dictionary-style string with name, label, color
conbined = []
for i in range(len(groups)):
conbined.append(group_template.format(name=groups[i], label=labels[i], color=colors_n[i]))
group_text = ",".join(conbined)
# id_list: Values for "id" column
# : Sorted without duplicates
id_list = []
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])] # iid: column value for "id" title
if iid != "":
id_list.append(iid)
id_list = list(set(id_list))
id_list.sort()
# option_keys: Store the option keys of the positions dictionary
option_keys = tools.dict_keys(cols_di) # option_keys: list: sorted keys of cols_di
option_keys.remove("id") # option key
option_keys.remove("chr1") # must key
option_keys.remove("break1") # must key
option_keys.remove("chr2") # must key
option_keys.remove("break2") # must key
if "group" in option_keys:
option_keys.remove("group") # option key
# node_size: Size to divide chromosomes
node_size_select = tools.config_getint(config, "ca", "selector_split_size", 5000000)
# Write header and dataset of JavaScript file
f = open(output_file, "w")
f.write(js_header + js_dataset.format(
node_size_detail=calc_node_size(genome_size, 500), # node size for detailed thumbnails
node_size_thumb=calc_node_size(genome_size, 250), # node size for rough thumbnails
node_size_select=node_size_select, # node size for bar graph
genome_size=genome, # A dictionary-style string containing keys of "chr", "size", "color", and "label"
IDs=convert.list_to_text(id_list), # A comma-separated string of id column values
group=group_text, # A dictionary-style string containing keys of "name", "label", and "color"
tooltip=convert.pyformat_to_jstooltip_text(cols_di, config, "ca", "result_format_ca", "tooltip_format"), # A dictionary-style string containing keys of "name", "label", and "color"
link_header=convert.list_to_text(option_keys),
))
# Write link of JavaScript file
f.write(js_links_1) # Write the leading part
data_links = []
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])] # iid: the value of "id" column
# Ignore empty string
if iid == "":
continue
chr1 = str(row[df.name_to_index(cols_di["chr1"])]) # chromosome1
pos1 = row[df.name_to_index(cols_di["break1"])] # break point1
chr2 = str(row[df.name_to_index(cols_di["chr2"])]) # chromosome2
pos2 = row[df.name_to_index(cols_di["break2"])] # break point2
# Check if chr1 and chr2 is in the genome list
# Check if pos1 and pos2 is in the chr1 length
# index1 and index2 are indexes of the genome_size for chr1 and chr2
[index1, rang] = insite_genome(genome_size, chr1, pos1)
if rang > 0:
print("breakpoint 1 is over range. chr%s: input=%d, range=%d" % (chr1, pos1, rang))
continue
if rang < 0:
#print("chr1 is undefined. %s" % (chr1))
continue
[index2, rang] = insite_genome(genome_size, chr2, pos2)
if rang > 0:
print("breakpoint 2 is over range. chr%s: input=%d, range=%d" % (chr2, pos2, rang))
continue
if rang < 0:
#print("chr2 is undefined. %s" % (chr2))
continue
# Whether chr1 and chr2 are the same chromosome
inner_flg = "false"
if (chr1 == chr2):
inner_flg = "true"
# Set group_id: -1, 0, 1, index values of groups
# : Sequential numbers identifying groups
group_id = -1 # Not belong to any groups
if "group" in cols_di:
# If the value of group column is in group list, then group_id is the index of the list
# Others, group_id is -1
group_id = convert.value_to_index(groups, row[df.name_to_index(cols_di["group"])], -1)
else:
if inner_flg == "false":
group_id = 0 # chr1 and chr2 are in the different group
else:
group_id = 1 # chr1 and chr2 are in the same group
# Add an element to data_links
data_links.append([iid, index1, pos1, index2, pos2, group_id])
# tooltip_items: Data for tooltip
tooltip_items = []
for k in range(len(option_keys)): # Loop in the column titles except group, id, and must keys (chr1, chr2, break1, and break2)
key = option_keys[k]
if cols_di[key] == "":
continue
tooltip_items.append(row[df.name_to_index(cols_di[key])])
# Write link
f.write(links_template.format(
ID=iid,
Chr1=index1, pos1=pos1, Chr2=index2, pos2=pos2,
inner_flg=inner_flg,
group_id=group_id,
tooltip="[" + convert.list_to_text(tooltip_items) + "],"))
f.write(js_links_2) # Write the ending part
# Write integral bar item
# link: [{bp1: iid, bp2: iid}, {...}, ...]
# : Separate elements by group_id
link = []
for g in range(len(groups)):
link.append({})
for dl in data_links:
# dl = [iid, index1, pos1, index2, pos2, group_id]
# iid : The value of id title
# index1/2: The index of genome_size
# pos1/2 : Bareak point
# group_id: Index of groups
# Chr: The index of genome_size
# Pos: A break position based on node
bp1 = "root.{Chr:0>2}.{Chr:0>2}_{Pos:0>3}".format(Chr=dl[1], Pos=int(math.floor(dl[2] / node_size_select)))
bp2 = "root.{Chr:0>2}.{Chr:0>2}_{Pos:0>3}".format(Chr=dl[3], Pos=int(math.floor(dl[4] / node_size_select)))
group_id = dl[5]
# For bp1
if bp1 not in link[group_id]:
link[group_id][bp1] = []
link[group_id][bp1].append(dl[0]) # Append iid
# For bp2
if bp1 != bp2:
if bp2 not in link[group_id]:
link[group_id][bp2] = []
link[group_id][bp2].append(dl[0]) # Append iid
select_value_text = ""
select_key_text = ""
select_item_text = ""
for i in range(len(groups)):
values = [] # [Number of id, ...]
keys = [] # [[genome_size index, Break position], ...]
items = [] # [[id_list index, ...], ...]
for bp in sorted(link[i].keys()):
# values element
# link[i][bp]: list that stores id column values at a break position of a chromosome in a group
# : Duplicate values are stored
values.append(len(link[i][bp]))
# keys element
parts = bp.split(".")[2].split("_") # parts: [Chr, Pos]
keys.append([int(parts[0]), int(parts[1])])
# items element
sort = sorted(list(set(link[i][bp]))) # Delete duplicates
temp = []
for t in sort:
temp.append(id_list.index(t)) # id_list that stores values of id column
items.append(temp)
select_value_text += "[%s]," % (",".join(map(str, values)).replace(" ", "")) # += [1,1,...],
select_key_text += "[%s]," % (",".join(map(str, keys)).replace(" ", "")) # += [[0,1],[0,25],...],
select_item_text += "[%s]," % (",".join(map(str, items)).replace(" ", "")) # += [[9],[8],...],
f.write(js_selection.format(
value=select_value_text,
key=select_key_text,
item=select_item_text
))
# Write rest of JavaScript file and footer
f_template = open(os.path.dirname(os.path.abspath(__file__)) + "/templates/data_ca.js") # ./templates/data_ca.js
js_function = f_template.read()
f_template.close()
f.write(js_function)
f.write(js_footer)
f.close()
return {"id_list": id_list, "group_list": groups, "color": colors_n}
def convert_tojs(input_file, output_file, positions, config):
import os
import paplot.subcode.data_frame as data_frame
import paplot.subcode.merge as merge
import paplot.subcode.tools as tools
import paplot.convert as convert
cols_di = merge.position_to_dict(positions)
# data read
try:
df = data_frame.load_file(input_file, header = 1, \
sept = tools.config_getstr(config, "result_format_mutation", "sept"), \
comment = tools.config_getstr(config, "result_format_mutation", "comment") \
)
except Exception as e:
print ("failure open data %s, %s" % (input_file, e.message))
return None
if len(df.data) == 0:
print ("no data %s" % input_file)
return None
# func replace
for f in range(len(df.data)):
func_pos = df.name_to_index(cols_di["group"])
if df.data[f][func_pos] == "":
df.data[f][func_pos] = "_blank_"
[funcs, colors_n] = convert.group_list(df.column(cols_di["group"]), "mutation", "group", config)
# ID list
id_list = []
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid != "": id_list.append(iid)
id_list = list(set(id_list))
id_list.sort()
# gene list
genes = genes_list(df.column(cols_di["gene"]), \
df.column(cols_di["group"]), \
df.column(cols_di["id"]), \
funcs, id_list, config)
option_keys = tools.dict_keys(cols_di)
option_keys.remove("id")
option_keys.remove("group")
option_keys.remove("gene")
# mutation list
f = open(output_file, "w")
f.write(js_header)
f.write(js_mutations_1)
mutations = {}
tooltips = {}
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid == "": continue
if (iid in mutations) == False:
mutations[iid] = {}
tooltips[iid] = {}
func_split = convert.text_to_list(row[df.name_to_index(cols_di["group"])], \
tools.config_getstr(config, "result_format_mutation", "sept_group"))
tooltip_items = []
for k in range(len(option_keys)):
key = option_keys[k]
if cols_di[key] == "": continue
tooltip_items.append(row[df.name_to_index(cols_di[key])])
for func in func_split:
if (func in mutations[iid]) == False:
mutations[iid][func] = {}
tooltips[iid][func] = {}
gene_split = convert.text_to_list(row[df.name_to_index(cols_di["gene"])], \
tools.config_getstr(config, "result_format_mutation", "sept_gene"))
for gene in gene_split:
if (gene in mutations[iid][func]) == False:
mutations[iid][func][gene] = 1
tooltips[iid][func][gene] = []
else:
mutations[iid][func][gene] += 1
tooltips[iid][func][gene].append(tooltip_items)
mutations_sum = 0
for iid in tools.dict_keys(mutations):
for func in tools.dict_keys(mutations[iid]):
for gene in tools.dict_keys(mutations[iid][func]):
idx_i = convert.value_to_index(id_list, iid, -1)
idx_f = convert.value_to_index(funcs, func, -1)
idx_g = convert.value_to_index(genes, gene, -1)
if idx_i >= 0 and idx_f >= 0 and idx_g >= 0:
tooltip_items = ""
for tips in tooltips[iid][func][gene]:
tooltip_items += "[" + convert.list_to_text(tips) + "],"
f.write(mu_mutations_template.format(ID = idx_i, \
func = idx_f , \
gene = idx_g, \
num = mutations[iid][func][gene],
tooltip = tooltip_items))
mutations_sum += mutations[iid][func][gene]
f.write(js_mutations_2.format(mutations_sum = mutations_sum))
# write id, func, gene ... list
f.write(js_dataset.format(
Ids = convert.list_to_text(id_list), \
genes = convert.list_to_text(convert.list_prohibition(genes)), \
funcs = convert.list_to_text(convert.list_prohibition(funcs)), \
func_colors_n = convert.list_to_text(colors_n), \
mutation_header = convert.list_to_text(option_keys), \
checker_title = convert.pyformat_to_jstooltip_text(cols_di, config, "mutation", "result_format_mutation", "tooltip_format_checker_title"), \
checker_partial = convert.pyformat_to_jstooltip_text(cols_di, config, "mutation", "result_format_mutation", "tooltip_format_checker_partial"), \
gene_title = convert.pyformat_to_jstooltip_text(cols_di, config, "mutation", "result_format_mutation", "tooltip_format_gene_title"), \
gene_partial = convert.pyformat_to_jstooltip_text(cols_di, config, "mutation", "result_format_mutation", "tooltip_format_gene_partial"), \
id_title = convert.pyformat_to_jstooltip_text(cols_di, config, "mutation", "result_format_mutation", "tooltip_format_id_title"), \
id_partial = convert.pyformat_to_jstooltip_text(cols_di, config, "mutation", "result_format_mutation", "tooltip_format_id_partial"), \
))
dataset = {}
##### subdata #####
f.write(js_subdata_1)
subdata = []
counter = 0
for sec in config.sections():
if sec.startswith("mutation_subplot_type1_"):
ret_val = load_subdata(id_list, sec, config)
if ret_val == None: continue
[data_text, item, colors_n, label, title] = ret_val
name = "sub%d" % (counter)
pos = 1
counter += 1
elif sec.startswith("mutation_subplot_type2_"):
ret_val = load_subdata(id_list, sec, config)
if ret_val == None: continue
[data_text, item, colors_n, label, title] = ret_val
name = "sub%d" % (counter)
pos = 2
counter += 1
else: continue
f.write(subdata_template.format(name = name, \
title = title, \
type = tools.config_getstr(config, sec, "mode"), \
item = convert.list_to_text(item), \
label = convert.list_to_text(label), \
colors_n = convert.list_to_text(colors_n), \
data = data_text ))
subdata.append({"pos":pos, "label":label, "color":colors_n, "title": title})
f.write(js_subdata_2)
##### functions #####
f_template = open(os.path.dirname(os.path.abspath(__file__)) + "/templates/data_mutation.js")
js_function = f_template.read()
f_template.close()
f.write(js_function)
f.write(js_footer)
f.close()
dataset["subdata"] = subdata
return dataset
def convert_tojs(input_file, output_file, positions, config):
import os
import paplot.subcode.data_frame as data_frame
import paplot.subcode.merge as merge
import paplot.subcode.tools as tools
import paplot.convert as convert
import paplot.color as color
cols_di = merge.position_to_dict(positions)
# data read
try:
df = data_frame.load_file(input_file, header = 1, \
sept = tools.config_getstr(config, "result_format_qc", "sept"), \
comment = tools.config_getstr(config, "result_format_qc", "comment") \
)
except Exception as e:
print("failure open data %s, %s" % (input_file, e.message))
return None
if len(df.data) == 0:
print("no data %s" % input_file)
return None
# chart list
plots_text = ""
plots_option = []
config_sections = config.sections()
config_sections.sort()
if "qc_chart_brush" in config_sections:
config_sections.remove("qc_chart_brush")
config_sections.insert(0, "qc_chart_brush")
for sec in config.sections():
if not sec.startswith("qc_chart_"):
continue
chart_id = sec.replace("qc_chart_", "chart_")
stack_id = []
label = []
colors_di = {}
counter = 0
for name_set in tools.config_getstr(config, sec,
"name_set").split(","):
name_set_split = convert.text_to_list(name_set, ":")
if len(name_set_split) == 0:
continue
stack_id.append("stack" + str(counter))
label.append(name_set_split[0])
if len(name_set_split) > 1:
colors_di[name_set_split[0]] = color.name_to_value(
name_set_split[1])
counter += 1
# fill in undefined items
colors_di = color.create_color_dict(label, colors_di,
color.metro_colors)
# dict to value
colors_li = []
for key in label:
colors_li.append(colors_di[key])
plots_text += plot_template.format(
chart_id = chart_id, \
title = tools.config_getstr(config, sec, "title"), \
title_y = tools.config_getstr(config, sec, "title_y"), \
stack = convert.pyformat_to_jstooltip_text(cols_di, config, sec, "result_format_qc", "stack"), \
stack_id = convert.list_to_text(stack_id), \
label = convert.list_to_text(label), \
color = convert.list_to_text(colors_li), \
tooltip = convert.pyformat_to_jstooltip_text(cols_di, config, sec, "result_format_qc", "tooltip_format"), \
)
plots_option.append(chart_id)
# ID list
id_list = []
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid != "": id_list.append(iid)
id_list = list(set(id_list))
id_list.sort()
# header
headers = tools.dict_keys(cols_di)
f = open(output_file, "w")
f.write(js_header)
f.write(js_dataset.format(IDs = convert.list_to_text(id_list), \
header = convert.list_to_text(headers), \
plots = plots_text))
f.write(js_data1)
# values
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid == "": continue
values = ""
for item in headers:
if len(values) > 0:
values += ","
val = row[df.name_to_index(cols_di[item])]
if type(val) == type(""):
values += "'" + val + "'"
elif type(val) == type(0.0):
values += str('%.2f' % val)
else:
values += str(val)
f.write("[" + values + "],")
f.write(js_data2)
f_template = open(
os.path.dirname(os.path.abspath(__file__)) + "/templates/data_qc.js")
js_function = f_template.read()
f_template.close()
f.write(js_function)
f.write(js_footer)
f.close()
return {"plots": plots_option}
def convert_tojs(input_file, output_file, positions, config):
import paplot.subcode.data_frame as data_frame
import paplot.subcode.merge as merge
import paplot.subcode.tools as tools
import paplot.convert as convert
import paplot.color as color
cols_di = merge.position_to_dict(positions)
# data read
try:
df = data_frame.load_file(input_file, header = 1, \
sept = tools.config_getstr(config, "merge_format_qc", "sept"), \
comment = tools.config_getstr(config, "result_format_qc", "comment") \
)
except Exception as e:
print ("failure open data %s, %s" % (input_file, e.message))
return None
if len(df.data) == 0:
print ("no data %s" % input_file)
return None
# chart list
plots_text = ""
plots_option = []
config_sections = config.sections()
config_sections.sort()
if "qc_chart_brush" in config_sections:
config_sections.remove("qc_chart_brush")
config_sections.insert(0, "qc_chart_brush")
for sec in config.sections():
if not sec.startswith("qc_chart_"):
continue
chart_id = sec.replace("qc_chart_", "chart_")
stack_id = []
label = []
colors_di = {}
counter = 0
for name_set in tools.config_getstr(config, sec, "name_set").split(","):
name_set_split = convert.text_to_list(name_set, ":")
if len(name_set_split) == 0:
continue
stack_id.append("stack" + str(counter))
label.append(name_set_split[0])
if len(name_set_split) > 1:
colors_di[name_set_split[0]] = color.name_to_value(name_set_split[1])
counter += 1
# fill in undefined items
colors_di = color.create_color_dict(label, colors_di, color.metro_colors)
# dict to value
colors_li = []
for key in label:
colors_li.append(colors_di[key])
plots_text += plot_template.format(
chart_id = chart_id, \
title = tools.config_getstr(config, sec, "title"), \
title_y = tools.config_getstr(config, sec, "title_y"), \
stack = convert.pyformat_to_jstooltip_text(cols_di, config, sec, "result_format_qc", "stack"), \
stack_id = convert.list_to_text(stack_id), \
label = convert.list_to_text(label), \
color = convert.list_to_text(colors_li), \
tooltip = convert.pyformat_to_jstooltip_text(cols_di, config, sec, "result_format_qc", "tooltip_format"), \
)
plots_option.append(chart_id)
# ID list
Ids = []
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid != "": Ids.append(iid)
Ids = list(set(Ids))
Ids.sort()
# header
headers = cols_di.keys()
headers.sort()
f = open(output_file, "w")
f.write(js_header)
f.write(js_dataset.format(IDs = convert.list_to_text(Ids), \
header = convert.list_to_text(headers), \
plots = plots_text))
f.write(js_data1)
# values
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid == "": continue
values = ""
for item in headers:
if len(values) > 0:
values += ","
val = row[df.name_to_index(cols_di[item])]
if type(val) == type(""):
values += "'" + val + "'"
elif type(val) == type(0.0):
values += str('%.2f' % val)
else:
values += str(val)
f.write("[" + values + "],")
f.write(js_data2)
f.write(js_function)
f.close()
return {"plots": plots_option}
def convert_tojs(input_file, output_file, positions, config):
import paplot.subcode.data_frame as data_frame
import paplot.subcode.merge as merge
import paplot.subcode.tools as tools
import paplot.convert as convert
genome_size = load_genome_size(config)
if len(genome_size) == 0:
return None
genome = ""
for i in range(len(genome_size)):
if len(genome) > 0:
genome += ",\n"
genome += genome_size_template.format(Chr=i, size = genome_size[i][1], color = genome_size[i][2], label = genome_size[i][3])
cols_di = merge.position_to_dict(positions)
# data read
try:
df = data_frame.load_file(input_file, header = 1, \
sept = tools.config_getstr(config, "merge_format_sv", "sept"), \
comment = tools.config_getstr(config, "result_format_sv", "comment") \
)
except Exception as e:
print ("failure open data %s, %s" % (input_file, e.message))
return None
if len(df.data) == 0:
print ("no data %s" % input_file)
return None
# group list
if "group" in cols_di:
for f in range(len(df.data)):
group_pos = df.name_to_index(cols_di["group"])
group = df.data[f][group_pos]
df.data[f][group_pos] = group.replace(" ", "_")
if group == "":
df.data[f][group_pos] = "_blank_"
[groups, colors_n] = convert.group_list(df.column(cols_di["group"]), "sv", "group", config)
labels = groups
else:
groups = ["outer", "inner"]
labels = ["Inter Chromosome", "Intra Chromosome"]
colors_n = ["#9E4A98", "#51BF69"]
conbined = []
for i in range(len(groups)):
conbined.append(group_template.format(name = groups[i], label = labels[i], color = colors_n[i]))
group_text = ",".join(conbined)
# ID list
Ids = []
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid != "": Ids.append(iid)
Ids = list(set(Ids))
Ids.sort()
option_keys = cols_di.keys()
option_keys.remove("id")
option_keys.remove("chr1")
option_keys.remove("break1")
option_keys.remove("chr2")
option_keys.remove("break2")
if "group" in option_keys:
option_keys.remove("group")
f = open(output_file, "w")
f.write(js_header \
+ js_dataset.format(node_size_detail = calc_node_size(genome_size, 500), \
node_size_thumb = calc_node_size(genome_size, 250), \
node_size_select = tools.config_getint(config, "sv", "selector_split_size", 5000000),\
genome_size = genome, \
IDs = convert.list_to_text(Ids), \
group = group_text, \
tooltip = convert.pyformat_to_jstooltip_text(cols_di, config, "sv", "result_format_sv", "tooltip_format"), \
link_header = convert.list_to_text(option_keys), \
))
# write links
f.write(js_links_1)
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid == "": continue
chr1 = str(row[df.name_to_index(cols_di["chr1"])])
pos1 = row[df.name_to_index(cols_di["break1"])]
chr2 = str(row[df.name_to_index(cols_di["chr2"])])
pos2 = row[df.name_to_index(cols_di["break2"])]
[index1, rang] = insite_genome(genome_size, chr1, pos1)
if rang > 0:
print("breakpoint 1 is over range. chr%s: input=%d, range=%d" % (chr1, pos1, rang))
continue
if rang < 0:
#print("chr1 is undefined. %s" % (chr1))
continue
[index2, rang] = insite_genome(genome_size, chr2, pos2)
if rang > 0:
print("breakpoint 2 is over range. chr%s: input=%d, range=%d" % (chr2, pos2, rang))
continue
if rang < 0:
#print("chr2 is undefined. %s" % (chr2))
continue
inner_flg = "false"
if (chr1 == chr2):
inner_flg = "true"
tooltip_items = []
for k in range(len(option_keys)):
key = option_keys[k]
if cols_di[key] == "": continue
tooltip_items.append(row[df.name_to_index(cols_di[key])])
group_id = -1
if "group" in cols_di:
group_id = convert.value_to_index(groups, row[df.name_to_index(cols_di["group"])], -1)
else:
if inner_flg == "false":
group_id = 0
else:
group_id = 1
f.write(links_template.format(ID = iid, \
Chr1=index1, pos1=pos1, Chr2=index2, pos2=pos2, \
inner_flg = inner_flg, \
group_id = group_id , \
tooltip = "[" + convert.list_to_text(tooltip_items) + "],"))
f.write(js_links_2)
f.write(js_function)
f.close()
return {"id_list":Ids, "group_list":groups, "color":colors_n}
def convert_tojs(input_file, output_file, positions, config):
import paplot.subcode.data_frame as data_frame
import paplot.subcode.merge as merge
import paplot.subcode.tools as tools
import paplot.convert as convert
import math
genome_size = load_genome_size(config)
if len(genome_size) == 0:
return None
genome = ""
for i in range(len(genome_size)):
if len(genome) > 0:
genome += ",\n"
genome += genome_size_template.format(Chr=i,
size=genome_size[i][1],
color=genome_size[i][2],
label=genome_size[i][3])
cols_di = merge.position_to_dict(positions)
# data read
try:
df = data_frame.load_file(input_file, header = 1, \
sept = tools.config_getstr(config, "result_format_ca", "sept"), \
comment = tools.config_getstr(config, "result_format_ca", "comment") \
)
except Exception as e:
print("failure open data %s, %s" % (input_file, e.message))
return None
if len(df.data) == 0:
print("no data %s" % input_file)
return None
# group list
if "group" in cols_di:
for f in range(len(df.data)):
group_pos = df.name_to_index(cols_di["group"])
group = df.data[f][group_pos]
df.data[f][group_pos] = group.replace(" ", "_")
if group == "":
df.data[f][group_pos] = "_blank_"
[groups, colors_n] = convert.group_list(df.column(cols_di["group"]),
"ca", "group", config)
labels = groups
else:
groups = ["outer", "inner"]
labels = ["Inter-chromosome", "Intra-chromosome"]
colors_n = ["#9E4A98", "#51BF69"]
conbined = []
for i in range(len(groups)):
conbined.append(
group_template.format(name=groups[i],
label=labels[i],
color=colors_n[i]))
group_text = ",".join(conbined)
# ID list
Ids = []
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid != "": Ids.append(iid)
Ids = list(set(Ids))
Ids.sort()
option_keys = tools.dict_keys(cols_di)
option_keys.remove("id")
option_keys.remove("chr1")
option_keys.remove("break1")
option_keys.remove("chr2")
option_keys.remove("break2")
if "group" in option_keys:
option_keys.remove("group")
# node_size
node_size_select = tools.config_getint(config, "ca", "selector_split_size",
5000000)
f = open(output_file, "w")
f.write(js_header \
+ js_dataset.format(node_size_detail = calc_node_size(genome_size, 500), \
node_size_thumb = calc_node_size(genome_size, 250), \
node_size_select = node_size_select,\
genome_size = genome, \
IDs = convert.list_to_text(Ids), \
group = group_text, \
tooltip = convert.pyformat_to_jstooltip_text(cols_di, config, "ca", "result_format_ca", "tooltip_format"), \
link_header = convert.list_to_text(option_keys), \
))
# write links
data_links = []
f.write(js_links_1)
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid == "": continue
chr1 = str(row[df.name_to_index(cols_di["chr1"])])
pos1 = row[df.name_to_index(cols_di["break1"])]
chr2 = str(row[df.name_to_index(cols_di["chr2"])])
pos2 = row[df.name_to_index(cols_di["break2"])]
[index1, rang] = insite_genome(genome_size, chr1, pos1)
if rang > 0:
print("breakpoint 1 is over range. chr%s: input=%d, range=%d" %
(chr1, pos1, rang))
continue
if rang < 0:
#print("chr1 is undefined. %s" % (chr1))
continue
[index2, rang] = insite_genome(genome_size, chr2, pos2)
if rang > 0:
print("breakpoint 2 is over range. chr%s: input=%d, range=%d" %
(chr2, pos2, rang))
continue
if rang < 0:
#print("chr2 is undefined. %s" % (chr2))
continue
inner_flg = "false"
if (chr1 == chr2):
inner_flg = "true"
tooltip_items = []
for k in range(len(option_keys)):
key = option_keys[k]
if cols_di[key] == "": continue
tooltip_items.append(row[df.name_to_index(cols_di[key])])
group_id = -1
if "group" in cols_di:
group_id = convert.value_to_index(
groups, row[df.name_to_index(cols_di["group"])], -1)
else:
if inner_flg == "false":
group_id = 0
else:
group_id = 1
data_links.append([iid, index1, pos1, index2, pos2, group_id])
f.write(links_template.format(ID = iid, \
Chr1=index1, pos1=pos1, Chr2=index2, pos2=pos2, \
inner_flg = inner_flg, \
group_id = group_id , \
tooltip = "[" + convert.list_to_text(tooltip_items) + "],"))
f.write(js_links_2)
# integral bar item
link = []
for g in range(len(groups)):
link.append({})
for l in data_links:
bp1 = "root.{Chr:0>2}.{Chr:0>2}_{Pos:0>3}".format(
Chr=l[1], Pos=int(math.floor(l[2] / node_size_select)))
bp2 = "root.{Chr:0>2}.{Chr:0>2}_{Pos:0>3}".format(
Chr=l[3], Pos=int(math.floor(l[4] / node_size_select)))
group = l[5]
#print group
# add bp1
if not bp1 in link[group]:
link[group][bp1] = []
link[group][bp1].append(l[0])
# add bp2
if bp1 != bp2:
if not bp2 in link[group]:
link[group][bp2] = []
link[group][bp2].append(l[0])
select_item_text = ""
select_value_text = ""
select_key_text = ""
for g in range(len(groups)):
items = []
values = []
keys = []
for i in link[g]:
values.append(len(link[g][i]))
# split key to chr and pos
parts = i.split(".")[2].split("_")
keys.append([int(parts[0]), int(parts[1])])
# delete duplication
sort = sorted(list(set(link[g][i])))
temp = []
for t in sort:
temp.append(Ids.index(t))
items.append(temp)
select_value_text += "[%s]," % (",".join(map(str, values)).replace(
" ", ""))
select_key_text += "[%s]," % (",".join(map(str, keys)).replace(
" ", ""))
select_item_text += "[%s]," % (",".join(map(str, items)).replace(
" ", ""))
f.write(
js_selection.format(value=select_value_text,
key=select_key_text,
item=select_item_text))
f.write(js_function)
f.close()
return {"id_list": Ids, "group_list": groups, "color": colors_n}
def convert_tojs(input_file, output_file, positions, config):
import paplot.subcode.data_frame as data_frame
import paplot.subcode.merge as merge
import paplot.subcode.tools as tools
import paplot.convert as convert
cols_di = merge.position_to_dict(positions)
# data read
try:
df = data_frame.load_file(input_file, header = 1, \
sept = tools.config_getstr(config, "merge_format_mutation", "sept"), \
comment = tools.config_getstr(config, "result_format_mutation", "comment") \
)
except Exception as e:
print ("failure open data %s, %s" % (input_file, e.message))
return None
if len(df.data) == 0:
print ("no data %s" % input_file)
return None
# func replace
for f in range(len(df.data)):
func_pos = df.name_to_index(cols_di["func"])
func = df.data[f][func_pos]
df.data[f][func_pos] = func.replace(" ", "_")
if func == "":
df.data[f][func_pos] = "_blank_"
[funcs, colors_n] = convert.group_list(df.column(cols_di["func"]), "mut", "func", config)
# ID list
Ids = []
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid != "": Ids.append(iid)
Ids = list(set(Ids))
Ids.sort()
genes = genes_list(df.column(cols_di["gene"]), \
df.column(cols_di["func"]), \
df.column(cols_di["id"]), \
funcs, Ids, config)
option_keys = cols_di.keys()
option_keys.remove("id")
option_keys.remove("func")
option_keys.remove("gene")
f = open(output_file, "w")
f.write(js_header \
+ js_dataset.format(Ids = convert.list_to_text(Ids), \
genes = convert.list_to_text(genes), \
funcs = convert.list_to_text(funcs), \
func_colors_n = convert.list_to_text(colors_n), \
mutation_header = convert.list_to_text(option_keys), \
checker_title = convert.pyformat_to_jstooltip_text(cols_di, config, "mut", "result_format_mutation", "tooltip_format_checker_title"), \
checker_partial = convert.pyformat_to_jstooltip_text(cols_di, config, "mut", "result_format_mutation", "tooltip_format_checker_partial"), \
gene_title = convert.pyformat_to_jstooltip_text(cols_di, config, "mut", "result_format_mutation", "tooltip_format_gene_title"), \
gene_partial = convert.pyformat_to_jstooltip_text(cols_di, config, "mut", "result_format_mutation", "tooltip_format_gene_partial"), \
id_title = convert.pyformat_to_jstooltip_text(cols_di, config, "mut", "result_format_mutation", "tooltip_format_id_title"), \
id_partial = convert.pyformat_to_jstooltip_text(cols_di, config, "mut", "result_format_mutation", "tooltip_format_id_partial"), \
))
# mutation list
f.write(js_mutations_1)
mutations = {}
tooltips = {}
for row in df.data:
iid = row[df.name_to_index(cols_di["id"])]
if iid == "": continue
if (iid in mutations) == False:
mutations[iid] = {}
tooltips[iid] = {}
func_split = convert.text_to_list(row[df.name_to_index(cols_di["func"])], \
tools.config_getstr(config, "result_format_mutation", "sept_func"))
tooltip_items = []
for k in range(len(option_keys)):
key = option_keys[k]
if cols_di[key] == "": continue
tooltip_items.append(row[df.name_to_index(cols_di[key])])
for func in func_split:
if (func in mutations[iid]) == False:
mutations[iid][func] = {}
tooltips[iid][func] = {}
gene_split = convert.text_to_list(row[df.name_to_index(cols_di["gene"])], \
tools.config_getstr(config, "result_format_mutation", "sept_gene"))
for gene in gene_split:
if (gene in mutations[iid][func]) == False:
mutations[iid][func][gene] = 1
tooltips[iid][func][gene] = []
else:
mutations[iid][func][gene] += 1
tooltips[iid][func][gene].append(tooltip_items)
mutations_sum = 0
for iid in mutations:
for func in mutations[iid]:
for gene in mutations[iid][func]:
idx_i = convert.value_to_index(Ids, iid, -1)
idx_f = convert.value_to_index(funcs, func, -1)
idx_g = convert.value_to_index(genes, gene, -1)
if idx_i >= 0 and idx_f >= 0 and idx_g >= 0:
tooltip_items = ""
for tips in tooltips[iid][func][gene]:
tooltip_items += "[" + convert.list_to_text(tips) + "],"
f.write(mu_mutations_template.format(ID = idx_i, \
func = idx_f , \
gene = idx_g, \
num = mutations[iid][func][gene],
tooltip = tooltip_items))
mutations_sum += mutations[iid][func][gene]
f.write(js_mutations_2.format(mutations_sum = mutations_sum))
dataset = {"func":funcs, "color":colors_n}
##### subdata #####
f.write(js_subdata_1)
subdata = []
counter = 0
for sec in config.sections():
if sec.startswith("mut_subplot_type1_"):
ret_val = load_subdata(Ids, sec, config)
if ret_val == None: continue
[data_text, item, colors_n, label, title] = ret_val
name = "sub%d" % (counter)
pos = 1
counter += 1
elif sec.startswith("mut_subplot_type2_"):
ret_val = load_subdata(Ids, sec, config)
if ret_val == None: continue
[data_text, item, colors_n, label, title] = ret_val
name = "sub%d" % (counter)
pos = 2
counter += 1
else: continue
f.write(subdata_template.format(name = name, \
title = title, \
type = tools.config_getstr(config, sec, "mode"), \
item = convert.list_to_text(item), \
label = convert.list_to_text(label), \
colors_n = convert.list_to_text(colors_n), \
data = data_text ))
subdata.append({"pos":pos, "label":label, "color":colors_n, "title": title})
f.write(js_subdata_2)
##### functions #####
f.write(js_function)
f.close()
dataset["subdata"] = subdata
return dataset
