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motif_vis.py
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#######################################################################
#Author: Dewan Shrestha #
#PI : Yong Cheng ([email protected]) #
#######################################################################
import sys
import os
script_path = os.path.dirname(os.path.realpath(__file__))
sys.path.append(script_path)
sys.path.append(script_path+'/scripts')
from utils import *
import argparse
import dash
import dash_core_components as dcc
import dash_html_components as html
import dash_bootstrap_components as dbc
from dash.dependencies import Input, Output, State
import webbrowser
from dash.exceptions import PreventUpdate
############################################### initial arguments ##############################
parser = argparse.ArgumentParser()
parser.add_argument('-i', '--input', default=None, help='multiple alignment format file for visualization')
parser.add_argument('-m','--motif', default=None, help='user defined motif, must be in meme format')
parser.add_argument('-d','--dir', default='motif_vis_temp_files', help='folder name for the temporary files generated during the process')
parser.add_argument('-l','--load', default = True, help='automatically opens browser if value is true')
parser.add_argument('-f','--format', default='maf', choices=['maf','clustal', 'fasta'],help='format of the alignment file')
parser.add_argument('-t','--thresh', default='1e-4', help='default threshold value is 1e-4 for fimo scan')
args = parser.parse_args()
#creating log file
logger_path = os.path.abspath(args.dir)
logger.add(logger_path+'/visualization_{time}.log', rotation='10 MB')
#if output directory is not present, creates a new directory
if not os.path.exists(args.dir):
os.makedirs(args.dir)
if args.input == None:
logger.info('using default example')
extract_seq_from_maf(script_path+'/example_files/example.maf', args.dir)
aln = AlignIO.read(os.path.join(args.dir,'temp_aln.fa'),'fasta')
#parser.print_help()
#sys.exit()
else:
if args.format=='maf':
extract_seq_from_maf(args.input, args.dir) # processing the maf file to combine alignment blocks
aln = AlignIO.read(os.path.join(args.dir,'temp_aln.fa'),'fasta')
elif args.format == 'clustal':
extract_seq_from_clustal(args.input, args.dir)
aln = AlignIO.read(os.path.join(args.dir,'temp_aln.fa'),'fasta')
elif args.format == 'fasta':
aln = AlignIO.read(args.input,'fasta')
with open(os.path.join(args.dir ,'fimo_input.fa'),'w') as f:
file_ = open(args.input).read().replace('-','')
f.write(file_)
else:
logger.info('the format is not supported, please use the supported format file')
sys.exit()
# checks if user has provided own motif or not, it has to be in meme format
if args.motif == None:
motif_shown = ['MA0139.1'] #, 'MA0035.4','MA0138.2']
else:
motif_shown=[]
custom_motif = open(args.motif).read().split('MOTIF')
for n in range(1, len(custom_motif)):
data = custom_motif[n].split('\n')[0].split()
key = data[0]
jasper_dict[key]= {'motif_name':data[1], 'species':'c', 'pwm':'MOTIF'+custom_motif[n]}
motif_shown.append(key)
#creating lists for tf and species for dash dropdown options
motif_options = [{'label':'{} ({})'.format(jasper_dict[key]['motif_name'],jasper_dict[key]['species'] ), 'value':key} for key,value in jasper_dict.items()]
species_options= [{'label':value, 'value':key} for key, value in species_dict.items()]
logger.info('options created for the buttons')
#extracting sequences and ids from the alignment file
#aln = AlignIO.read(os.path.join(args.dir,'temp_aln.fa'),'fasta')
seqs, seq_ids, nucleotide_bases, seq_names, sp_names = [], [], [], [], []
for rec in aln:
seqs.append(rec.seq)
seq_ids.append(rec.id.lower())
for s in seq_ids:
for sp in species_options:
if sp['value'].lower() in s:
seq_names.append([sp['label'], s])
sp_names.append(sp['label'])
logger.info('all the species found')
logger.info(sp_names)
for s in seqs:
nucleotide_bases.append([i for i in s])
#nucleotide_bases2 = [item for sublist in nucleotide_bases for item in sublist]
seq_len = len(nucleotide_bases[0])
default_base_values = [[0]*seq_len for x in range(len(nucleotide_bases))]
hover_data= [['']*seq_len for x in range(len(nucleotide_bases))]
#y = [[i[0]]*seq_len for i in seq_names]
#y = [item for sublist in y for item in sublist]
app = dash.Dash(external_stylesheets=[dbc.themes.BOOTSTRAP])
################################## top header ########################################
top_header= dbc.Row(dbc.Col(html.H1('ATM Viewer',
style={'textAlign':'center',
'marginTop':5,
'marginBottom':10,
'paddingBottom':5,
'fontFamily':'Courier New',
'fontWeight':'bold',
'fontColor':'#FF0000'
})))
################################### empty row at the end #############################
empty_row = dbc.Row(dbc.Col(html.P('.',style={'marginTop':10,
'fontSize':5})))
################################### dropdown options #############################################
dropdown = html.Div([
html.H3('Select the TF you want to search for:',
style={'marginTop':15,
'paddingLeft':10,
'fontSize':20,
'fontFamily':'Courier New',
'fontWeight':'bold'
}),
dcc.Dropdown(id='motif_id',
options=motif_options,
multi=True,
value= motif_shown,
style={'marginTop':5,
'paddingTop':5,
'paddingBottom':5,
'paddingLeft':10}
),
html.Button(id='submit', n_clicks=0, children='Submit',
style={'fontSize':20,
'paddingLeft':10,
'marginLeft':10,
'fontFamily':'Courier New'}),
dcc.Loading(id='fimo_running',
children=[html.Div(id='fimo_status',
style={'paddingLeft':10,
'paddingTop':10
})]),
html.H3('Select the species you want to view:',
style={'marginTop':20,
'marginBottom':5,
'fontSize':20,
'fontFamily':'Courier New',
'fontWeight':'bold',
'paddingLeft':10
}),
dcc.Dropdown(id='species_id',
options=species_options,
multi=True,
value=['hg','mm', 'pantro', 'gorgor', 'rhemac'],
style={'marginTop':10,
'paddingTop':5,
'paddingBottom':5,
'paddingLeft':10}
)
])
######################################### figure bar legend #######################################
heatmap_legend = html.Div([
dcc.Graph(id='figure_bar',
config={'toImageButtonOptions':{'format':'svg'},
'displayModeBar':True}
)
], style={'paddingRight':10,
'paddingLeft':0,
'marginLeft':0
})
tree = html.Div([
dcc.Graph(id='tree',
config={'toImageButtonOptions':{'format':'svg'},
'displayModeBar':True}
)
],style={
'paddingRight':0,
'marginRight':0
})
###################################### [motif informations: seleected vs found] and [species] ############
tf_selected = [
dbc.CardHeader("TF Selected"),
dbc.CardBody(
[
#html.H5("Card title", className="card-title"),
dcc.Markdown(id= 'tf_selected',
className="card-text",
)
]
)
]
tf_found = [
dbc.CardHeader("TF Found"),
dbc.CardBody(
[
#html.H5("Card title 2", className="card-title"),
dcc.Markdown(id='tf_found_ids',
className="card-text",
),
]
),
]
species_details = [
dbc.CardHeader("Details about species aligned"),
dbc.CardBody(
[
#html.H5("Card title 3", className="card-title"),
dcc.Markdown(id='species',children = get_markdown(seq_names, fimo=False),
className="card-text",
),
]
),
]
################################## cards with information about tfs found and species #######################
cards = html.Div(
[
dbc.Row(
[
dbc.Col(dbc.Card(tf_selected, color="info", inverse=True)),
dbc.Col(dbc.Card(tf_found, color="success", inverse=True))
],
className="mb-4"
),
dbc.Row(
[
dbc.Col(dbc.Card(species_details, color="secondary", inverse=True)),
],
className="mb-4")
], style={
'paddingLeft':10
})
description = html.Div(cards)
################################################# main alignment file ###############################
main_figure = html.Div([
dcc.Graph(id='motif_plot',
config={'toImageButtonOptions':{'format':'svg', 'height':500,'width':1100, 'filename':'motif'},
'displayModeBar':True
}
)
],style={
'paddingRight':10,
'marginBottom':30
})
end =dbc.Row(dbc.Col(html.P('.',style={'marginTop':10,
'fontSize':5})))
################################################### layout ########################################
body = html.Div(dbc.Row([
dbc.Col(dropdown, width=4),
dbc.Col(tree, width=3),
dbc.Col(heatmap_legend, width=5)
]))
graph = html.Div(dbc.Row([
dbc.Col(description, width=4),
dbc.Col(main_figure, width=8)
]))
#dcc.Store(id='store_data')
app.layout=html.Div([dcc.Store(id='memory-output'),
top_header, empty_row,body, graph, end
]
)
######################################################### callbacks #################################
@app.callback([Output('tf_selected','children'),
Output('tf_found_ids','children'),
Output('memory-output', 'data'),
Output('fimo_status','children')
],
[Input('submit','n_clicks')],
[State('motif_id','value')])
def tf_selected(n_clicks, value):
tf_selected = get_markdown(value)
if n_clicks > 0:
logger.info('\n\n------------number of clicks{}------------\n\n', n_clicks)
alert = dbc.Alert("Fimo run completed", color="success")
logger.info('running fimo')
pwm_file = extract_pwm(value, args.dir)
os_code, fimo_file = run_fimo(os.path.join(args.dir,'fimo_input.fa'), pwm_file, args.dir, args.thresh)
if os_code == 1:
logger.info('Something went wrong while running fimo')
sys.exit(1)
else:
logger.info('processing fimo')
fimo_ids, fimo_list, motif_species = process_fimo(fimo_file)
logger.info('fimo_ids\n{}',fimo_ids)
logger.info('fimolist\n{}', fimo_list)
tf_found_ = get_markdown(fimo_ids)
logger.info('\n\n------------ NUMBER OF TF FOUND : {}------------\n\n', len(fimo_ids))
logger.info('tf found\n{}', tf_found_)
#print(hover_data[0])
base_color_values, hover_values, colorscale, legend_col = get_intermediate_data(fimo_ids, fimo_list, default_base_values, hover_data, nucleotide_bases)
#logger.info('hover values \n{}',hover_values)
#logger.info('\nhover_data \n {}', hover_data)
#logger.info('colorscale\n{}',colorscale)
#logger.info('legend_col\n{}', legend_col)
data = [{'base_values':base_color_values}, {'hover_values':hover_values},{'nucleotide_bases':nucleotide_bases},{'sp_names':sp_names}, {'colorscale':colorscale},{'legend_col':legend_col}, {'motif_species':motif_species},{'tf_selected':value}]
else:
tf_found_ =[None]
alert = dbc.Alert("Press submit to run fimo", color="info")
data=None
#'''.format(motif_names[value[0]], motif_names[value[1]])
#return 'The motifs selected are: {}'.format(', '.join([jasper_dict[i]['motif_name'] for i in value]))
return tf_selected, tf_found_ , data, alert
@app.callback([Output('motif_plot','figure'),
Output('figure_bar','figure'),
Output('tree', 'figure')
],
[Input('species_id','value'),
Input('memory-output','data')])
def create_motif_plot(species_selected, data):
if data is None:
raise PreventUpdate
indices=[]
#print('species_selected',species_selected)
for n in species_selected:
try:
indices.append(sp_names.index(species_dict[n]))
except:
continue
#print(indices)
return get_figure(data, indices)
if __name__ == '__main__':
if args.load == True:
webbrowser.open_new('http://127.0.0.1:8051')
app.run_server(debug=True, port=8051)
else:
app.run_server(debug=True, port=8051)