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BAMdelbee-Application.py
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BAMdelbee-Application.py
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#!/usr/bin/env python
# coding: utf-8
# In[ ]:
import pandas as pd
#import lxml, html5lib
import dash
from dash.dependencies import Input, Output
from dash import dcc, html, dash_table
from zipfile import ZipFile
from glob import glob
from time import sleep
import urllib
# In[ ]:
batches = glob("assets/*.zip")
omim_map = pd.read_csv('assets/OMIM_map.txt', sep = '\t')
MGI_IDs = pd.read_csv('assets/MGI_IDs.csv', dtype = str)
MGI_IDs = dict(zip(MGI_IDs['Symbol'], MGI_IDs['MGI_ID']))
hpo = pd.read_csv('assets/HPO_dict.txt', sep = '\t')
hpo = hpo[hpo['Associated Genes'].str.len() > 1]
refSeqSummaries = pd.read_csv('assets/RefSeqSummaries.tsv', sep = '\t', dtype = str)
default_style = {'width' : '57%', 'height' : '100%', 'margin' : '10px', 'font-family' : 'gisha', 'marginLeft' : 'auto', 'marginRight' : 'auto', 'textAlign' : 'center'}
default_style = {'width' : '100%', 'height' : '100%', 'margin' : '10px', 'font-family' : 'gisha', 'marginLeft' : 'auto', 'marginRight' : 'auto', 'textAlign' : 'center'}
hide = {'display' : 'None'}
full_display = {'width' : '100%', 'height' : '100%', 'margin' : '10px', 'font-family' : 'gisha', 'textAlign' : 'center'}
info_style = {'width' : '100%', 'height' : '100%', 'margin' : '10px', 'font-family' : 'gisha', 'marginLeft' : 'auto', 'marginRight' : 'auto', 'textAlign' : 'left'}
break_line = html.Hr(style={'height' : '4px', 'width' : '60%', 'color' : '#111111','display' : 'inline-block', 'marginLeft':'auto', 'marginRight':'auto'})
# In[ ]:
def generateHeatTable(gene, Chromosome, Position):
df = pd.read_csv('assets/CleanerVar.tsv', sep = '\t')
df = df[df['Gene'] == gene]
if df.shape[0] == 0:
return html.P('Could not find pathogenic variants for this gene in ClinVar🤷 🤷♂️')
del df['Gene']
del df['Chromosome']
df.fillna('', inplace = True)
df['Reference'] = df['Reference'].astype(str).str.replace('na','')
df['Variant'] = df['Variant'].astype(str).str.replace('na','')
df['Variation'] = df.apply(lambda x : x['Reference'] + '>' + x['Variant'], axis = 1)
del df['Reference']
del df['Variant']
df['Variation'] = df.apply(lambda x : x['Mutation Type'] if x['Variation'] == '>' else x['Variation'], axis = 1)
del df['Mutation Type']
df['VariationID'] = df['VariationID'].apply(lambda x : str(int(x)))
df['Link'] = 'https://www.ncbi.nlm.nih.gov/clinvar/variation/' + df['VariationID']
del df['VariationID']
df = df.append({
'Significance' : '👩⚕️👨⚕️',
'Phenotypes' : '👩⚕️👨⚕️',
'Position' : int(Position),
'Variation' : 'Your variant',
'Link' : ''
}, ignore_index=True)
df.sort_values('Position', inplace = True)
if df['Position'].max() - int(Position) >= int(Position) - df['Position'].min():
maxSpace = df['Position'].max() - int(Position)
else:
maxSpace = int(Position) - df['Position'].min()
df['gradient'] = (1 - abs(int(Position) - df['Position']) / maxSpace) * 255 ** 0.7
df['gradient'] = df['gradient'].astype(int)
df.at[df.index[df['Position'] == Position].tolist(), 'gradient'] = 255
df['gradient'] = df['gradient'].apply(lambda x : 'rgb(255,' + str(255 - x) + ',' + str(255 - x)+')')
df['Position'] = df['Position'].apply(lambda x : str(Chromosome) + ':' + str(x))
cols = ('Position', 'Phenotypes', 'Variation', 'Link')
df['Variation'] = df['Variation'].apply(lambda x : x[:25] + '(...)' if len(x) > 25 else x)
return html.Table(
[html.Tr([html.Th(col) for col in cols], style = {'textAlign' : 'center', 'border': '1px solid black', 'border-collapse' : 'collapse'})] +
[html.Tr([
html.Td(df.iloc[i][col], style = {'backgroundColor' : df.iloc[i]['gradient'], 'textAlign' : 'center', 'border': '1px solid black', 'border-collapse' : 'collapse'}) if col != 'Link' else html.Td(html.A(href=df.iloc[i]['Link'], children=df.iloc[i][col], target='_blank'), style = {'backgroundColor' : df.iloc[i]['gradient'], 'textAlign' : 'center', 'border': '1px solid black', 'border-collapse' : 'collapse'}) for col in cols
]) for i in range(len(df))],
style = {'textAlign' : 'center', 'border': '1px solid black', 'border-collapse' : 'collapse'}
)
# In[ ]:
external_stylesheets = ['assets/BAMdelbee_main.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.title = "BAMdelbee | Ohad Birk's Lab"
app.config['suppress_callback_exceptions'] = False
# In[ ]:
app.layout = html.Div([
html.Div([
html.Img(id = 'header_image',
src = 'assets/logo_BAMdelbee.png',
style = {
'height' : '16%',
'width' : '16%',
'float' : 'left'
}
),
html.Span(''),
html.Img(id = 'header_image2',
src = 'assets/logo_birklab.png',
style = {
'height' : '20%',
'width' : '20%',
'float' : 'right',
'margin' : 4
}
),
]),
html.P(html.Br()),
html.H2(
'',
id = 'selected_batch',
style = {'width' : '100%', 'height' : '100%', 'font-family' : 'gisha', 'margin' : 'auto', 'textAlign' : 'center'}
),
html.P(
'Select sample/s:',
id = 'selected_samples',
style = {'display' : 'none'}
),
html.Div(
dcc.Dropdown(
id = 'BatchesDropdown',
options = [{'label': v[7:-4], 'value': v} for v in batches],
multi = False,
placeholder = 'Select a batch',
style = {'width' : '70%', 'height' : '100%', 'font-family' : 'gisha', 'margin' : 'auto', 'textAlign' : 'center'}
),
style = {'width' : '100%', 'height' : '100%', 'font-family' : 'gisha', 'margin' : 'auto', 'textAlign' : 'center'}
),
dcc.RadioItems(
id = 'referenceRadioButtons',
options=[
{'label': 'hg38', 'value': 'hg38'},
{'label': 'hg19', 'value': 'hg19'},
],
value='hg38',
labelStyle={'display': 'inline-block'},
style = default_style
),
html.P(html.Br(), id = 'temp_break'),
html.Div([
html.Div([
html.Div(id = 'checkListContainer'),
], id = 'checklist_div',
style = {'display' : 'None'}
)],
id = 'parameters_div',
style = default_style
),
html.Div(
dcc.Loading(
id = 'loading_results',
fullscreen = True,
children = [html.Div([html.Div(id = 'loading_table_results')])],
type = 'circle',
style = {'marginTop' : '120px'}
),
id = 'loading_results_div',
style={'width': '100%', 'height': '10%', 'borderWidth': '1px', 'borderStyle': 'grooved', 'borderRadius': '5px', 'textAlign': 'center', 'marginLeft':'auto', 'marginRight':'auto'}
),
html.Div(
dcc.Loading(
id = 'loading_heatTable',
fullscreen = True,
children = [html.Div([html.Div(id = 'loading_heattable_results')])],
type = 'circle',
style = {'marginTop' : '120px'}
),
id = 'loading_heatTable_div',
style={'width': '100%', 'height': '10%', 'borderWidth': '1px', 'borderStyle': 'grooved', 'borderRadius': '5px', 'textAlign': 'center', 'marginLeft':'auto', 'marginRight':'auto'}
),
html.Div(id = 'table_div', style = hide)
])
# In[ ]:
@app.callback(
[Output('BatchesDropdown', 'style'),
Output('referenceRadioButtons', 'style'),
Output('checklist_div', 'style'),
Output('selected_batch', 'children'),
Output('checkListContainer', 'children'),
Output('temp_break', 'style'),
Output('selected_samples', 'style')],
[Input('BatchesDropdown', 'value')]
)
def chooseBatch(batch):
if batch != None:
zBatch = ZipFile(batch)
samples = zBatch.read('samples.txt').decode('utf-8', 'ignore').split('\n')
samples = [{'label' : str(sample), 'value' : str(sample)} for sample in sorted(samples, reverse = True)]
checkList = dcc.Checklist(id = 'samplesCheckList', options = samples, labelStyle={'display': 'block'})
btn = html.Button('Analyze', id = 'Analysis_starting_button', disabled = True, n_clicks = 0, style = {'text-transform' : 'none', 'font-size' : '30px'})
checklist_style = {'width' : '100%', 'height' : '100%', 'font-family' : 'gisha', 'marginLeft' : 'auto', 'marginRight' : 'auto', 'textAlign' : 'center'}
return [hide, hide, checklist_style, batch[7:-4], [checkList, btn], {'display' : 'none'}, default_style]
else:
dropdown_style = {'width' : '70%', 'height' : '100%', 'font-family' : 'gisha', 'marginLeft' : 'auto', 'marginRight' : 'auto', 'textAlign' : 'center'}
ref_style = {'width' : '100%', 'height' : '100%', 'font-family' : 'gisha', 'marginLeft' : 'auto', 'marginRight' : 'auto', 'textAlign' : 'center'}
return [dropdown_style, ref_style, hide, '', None, default_style, {'display' : 'none'}]
@app.callback(
[Output('Analysis_starting_button', 'disabled')],
[Input('samplesCheckList', 'value')]
)
def chooseSamples(samples):
if samples not in [None, []]:
return [False]
else:
return [True]
@app.callback(
[Output('parameters_div', 'style'),
Output('table_div', 'style'),
Output('table_div', 'children'),
Output('loading_results_div', 'children'),
Output('selected_samples', 'children')],
[Input('Analysis_starting_button', 'n_clicks'),
Input('BatchesDropdown', 'value'),
Input('samplesCheckList', 'value'),
Input('referenceRadioButtons', 'value')]
)
def update_figure(clicks, batch, affected, referenceGenome):
if clicks in (0, None):
return [default_style, hide, [], None, 'Select sample\s:']
else:
if referenceGenome == 'hg38':
geneMap = pd.read_csv('assets/NCBI_Genes_hg38.map')
else:
geneMap = pd.read_csv('assets/NCBI_Genes_hg19.map')
geneMap['Chr'] = geneMap['Chr'].astype(str)
zBatch = ZipFile(batch)
deletions = []
sizes = []
genes = []
isCoding = []
exons = pd.read_csv('assets/' + referenceGenome + '_exons.csv.gz')
exons['Chromosome'] = exons['Chromosome'].astype(str)
for chromosome in [str(c) for c in range(1,23)] + ['X', 'Y']:
try:
df = pd.read_csv(zBatch.open('chr' + chromosome + '.coverage'), sep = '\t')
except:
continue
samples = df.columns[1:]
controls = [sample for sample in samples if sample not in affected]
for sample in affected:
df = df[df[sample] == 0]
for control in controls:
df = df[df[control] > 5]
if df.shape[0] < 2:
continue
coordinates = df['Coordinate'].tolist()
while len(coordinates) != 0:
for coordinate in coordinates:
start = coordinate
end = coordinate
while end + 50 in coordinates:
end = end + 50
coordinates = [coordinate for coordinate in coordinates if coordinate > end]
if end != start:
deletions.append(chromosome + ':' + str(start) + '-' + str(end))
sizes.append(end-start)
genes_in_deletion = geneMap[(geneMap['Chr'] == chromosome) & (geneMap['Start'] <= start) & (geneMap['End'] >= end)]['Gene'].tolist()
genes.append(', '.join(genes_in_deletion))
coding = exons[exons['Gene'].isin(genes_in_deletion)]
coding = coding[coding['Chromosome'] == chromosome]
coding = coding[(coding['Start'] >= start) & (coding['Start'] <= end)]
if coding.empty:
isCoding.append('')
else:
isCoding.append('Yes')
df = pd.DataFrame()
df['Coordinates'] = deletions
df['Chromosome'] = df['Coordinates'].apply(lambda x : int(x.split(':')[0].upper().replace('X', '23').replace('Y', '24').replace('M', '25').replace('MT', '25')))
df['~Size (bp)'] = sizes
df['Genes'] = genes
df['Start'] = df['Coordinates'].apply(lambda x : int(x.split(':')[1].split('-')[0]))
df.sort_values(['Chromosome', 'Start'], inplace = True)
df.reset_index(drop = True, inplace = True)
df['End'] = df['Coordinates'].apply(lambda x : int(x.split(':')[1].split('-')[1]))
df['Coding'] = isCoding
del df['Chromosome']
del df['Start']
del df['End']
df = df[df['~Size (bp)'] > 50]
df = df[df['Genes'] != '']
if df.empty:
return [hide, full_display, [html.H2('🤷 No deletion were found 🤷♂️')], None, ', '.join(affected)]
ddt = dash_table.DataTable(
id = 'table',
data = df.to_dict('records'),
columns = [{'id': c, 'name': c} for c in df.columns],
page_action = 'none',
row_selectable='single',
fixed_rows={'headers' : True},
style_cell = {
'textAlign': 'left',
'overflow': 'hidden',
'textOverflow': 'ellipsis',
'maxWidth': 0
},
tooltip_delay=0,
tooltip_duration=None,
style_data_conditional=[
{
'if': {'row_index': 'odd'},
'backgroundColor': 'rgb(247, 247, 255)'
},
{
'if': {'row_index': 'even'},
'backgroundColor': 'rgb(252, 252, 255)'
},
],
style_data={
'whiteSpace': 'normal',
'height': 'auto',
},
style_header = {
'backgroundColor': 'rgb(220, 220, 255)',
'fontWeight': 'bold',
'whiteSpace' : 'normal'
},
style_table={
'maxHeight': '250px',
'maxwidth' : '150%',
'border': 'thin lightgrey solid'
},
style_as_list_view = False
)
csv_report = df.fillna('').to_csv(na_rep = '', index = False).replace(',nan,', ',,').replace('[','').replace(']','').replace("'",'')
download_href = "data:text/csv;charset=utf-8," + urllib.parse.quote(csv_report)
download_image = html.A('Download table ⬇️', href = download_href, download = 'BAMdelbee_' + '_'.join(affected) + '.csv', title = 'Download table', style = {'text-decoration' : 'none', 'fontSize' : '150%', 'float' : 'right', 'marginTop' : 1})
info = html.Div('Click on a deletion for more information', id = 'info')
return [hide, full_display, [ddt, download_image, info], None, ', '.join(affected)]
@app.callback(
[Output('info', 'children'),
Output('info', 'style')],
[Input('table', 'derived_virtual_selected_rows'),
Input('table', 'derived_virtual_data'),
Input('referenceRadioButtons', 'value')]
)
def getVariantData(selected_row_index, data, referenceGenome):
if selected_row_index in [[], None]:
return [html.P('Select row for more information'), default_style]
else:
elements = []
coordinates = data[selected_row_index[0]]['Coordinates']
genes = data[selected_row_index[0]]['Genes']
#IGV & UCSC % gnomAD
igv_link = 'http://localhost:60151/goto?locus=chr' + coordinates
igvA = html.A('IGV', href = igv_link, target = '_blank')
ucsc_link = 'https://genome.ucsc.edu/cgi-bin/hgTracks?db=' + referenceGenome + '&position=' + coordinates.replace(':','%3A')
ucscA = html.A('UCSC', href = ucsc_link, target = '_blank')
if referenceGenome == 'hg38':
gnomAD_Url = 'https://gnomad.broadinstitute.org/region/' + coordinates + '?dataset=gnomad_r3'
else:
gnomAD_Url = 'https://gnomad.broadinstitute.org/region/' + coordinates + '?dataset=gnomad_r2_1'
gnomADLink = html.A('gnomAD',target='_blank', href = gnomAD_Url)
elements.append(html.Div([igvA, html.Span(' '), ucscA, html.Span(' '), gnomADLink]))
if len(genes) > 0:
#RefSeq
for gene in genes.split(', '):
try:
refseq = refSeqSummaries[refSeqSummaries['Symbol'] == gene]
fullName = refseq['Full Name'].tolist()[0]
elements.append(html.Div(fullName, style = {'fontStyle' : 'oblique'}))
summary = refseq['Summary'].tolist()[0]
elements.append(html.Div(summary))
elements.append(break_line)
except: False
#HPO
hpo_terms = hpo[hpo['Associated Genes'].str.contains('|'.join(genes.split(', ')))]['HPO'].tolist()
phenotypes = ', '.join(hpo_terms)
if len(phenotypes.strip()) > 0:
hpos = html.Details(
[
html.Summary('HPO associated phenotypes', style = {'fontStyle' : 'oblique'}),
html.Div(html.Div(phenotypes))
],
)
elements.append(hpos)
elements.append(break_line)
#GeneCards
geneCards = [html.Span('GeneCards: ')]
for gene in genes.split(', '):
geneCards_link = 'https://www.genecards.org/cgi-bin/carddisp.pl?gene=' + gene
geneCardsA = html.A(gene, href = geneCards_link, target = '_blank')
geneCards.append(html.Span(' '))
geneCards.append(geneCardsA)
elements.append(html.Div(geneCards))
#OMIM
omims = [html.Span('OMIM: ')]
for gene in genes.split(', '):
try:
omim = str(omim_map[omim_map['Approved Gene Symbol (HGNC)'] == gene]['MIM Number'].tolist()[0]).replace('.0','')
omim_link = 'https://omim.org/entry/' + omim
omimA = html.A(gene, href = omim_link, target = '_blank')
omims.append(html.Span(' '))
omims.append(omimA)
except: False
if len(omims) > 1:
elements.append(html.Div(omims))
#GTEx
GTExs = [html.Span('GTEx: ')]
for gene in genes.split(', '):
GTEx_link = 'https://gtexportal.org/home/gene/' + gene
GTExA = html.A(gene, href = GTEx_link, target = '_blank')
GTExs.append(html.Span(' '))
GTExs.append(GTExA)
elements.append(html.Div(GTExs))
#MGI
mgis = [html.Span('MGI: ')]
for gene in genes.split(', '):
try:
mgi_link = 'http://www.informatics.jax.org/marker/phenotypes/MGI:' + MGI_IDs[gene]
mgiA = html.A(gene, href = mgi_link, target = '_blank')
mgis.append(html.Span(' '))
mgis.append(mgiA)
except: False
if len(mgis) > 1:
elements.append(html.Div(mgis))
#ClinVar HeatTable
if len(genes) > 0:
elements.append(html.Div(break_line))
clinVarBtn = html.Button('ClinVar HeatTable', id = 'HeatTableBtn', n_clicks = 0, style = {'text-transform' : 'none'})
heatTableDiv = html.Div(id = 'heatTableDiv', style = {'display' : 'inline-block', 'margin':'auto'})
elements.append(clinVarBtn)
elements.append(heatTableDiv)
return [elements, info_style]
@app.callback(
[Output('heatTableDiv', 'children'),
Output('loading_heatTable_div', 'children'),
Output('HeatTableBtn', 'style')],
[Input('HeatTableBtn', 'n_clicks'),
Input('table', 'derived_virtual_selected_rows'),
Input('table', 'derived_virtual_data')]
)
def update_figure(clicks, selected_row_index, data):
if clicks in [0, None]:
return [[None], None, {'display' : 'inline-block', 'text-transform' : 'none'}]
else:
coordinates = data[selected_row_index[0]]['Coordinates']
gene = data[selected_row_index[0]]['Genes']
if ', ' in gene:
gene = gene.split(', ')[0]
return [generateHeatTable(gene, coordinates.split(':')[0], coordinates.split(':')[1].split('-')[0]), None, {'display' : 'None'}]
# In[ ]:
if __name__ == '__main__':
import webbrowser
webbrowser.open('http://127.0.0.1:6261/')
app.run_server(port=6261)