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Merge pull request #79 from Jumitti/beta
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Streamlit 1.40.1 and minors fix
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@Jumitti
Jumitti authored Nov 25, 2024
2 parents d985423 + 3661071 commit 13f0097
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Showing 4 changed files with 93 additions and 89 deletions.
142 changes: 74 additions & 68 deletions navigation/IMF.py
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Original file line number Diff line number Diff line change
Expand Up @@ -93,25 +93,24 @@ def email(excel_file, csv_file, txt_output, email_receiver, body, jaspar):
st.toast(f"Unknown error occurred: {e}")


def result_table_output(df):
source = df
def result_table_output(source):
score_range = source['Rel Score'].astype(float)
ystart = score_range.min() - 0.02
ystop = score_range.max() + 0.02
source['Gene_Region'] = source['Gene'] + " " + source['Species'] + " " + source['Region']
source['Beginning of sequences'] = source['Position']
if 'Rel Position' in source:
if "Rel Position" in source:
source['From TSS/gene end'] = source['Rel Position']
scale = alt.Scale(scheme='category10')
color_scale = alt.Color("Gene_Region:N", scale=scale)

gene_region_selection = alt.selection_point(fields=['Gene_Region'], on='click', bind='legend')

dropdown = alt.binding_select(
options=['Beginning of sequences', 'From TSS/gene end' if "Rel Position" in source else []],
options=['Beginning of sequences', 'From TSS/gene end'] if "Rel Position" in source else ['Beginning of sequences'],
name='(X-axis) Position from: ')

xcol_param = alt.param(value='Beginning of sequences', bind=dropdown)
xcol_param = alt.param(value='Beginning of sequences', bind=dropdown, name="x_axis")

chart = alt.Chart(source).mark_circle().encode(
x=alt.X('x:Q').title('Position (bp)'),
Expand All @@ -120,11 +119,12 @@ def result_table_output(df):
color=alt.condition(gene_region_selection, color_scale, alt.value('lightgray')),
tooltip=['Sequence', 'Position'] + (['Rel Position'] if "Rel Position" in source else []) + (
['Ch Position'] if "Ch Position" in source else []) + ['Rel Score'] + (
['p-value'] if 'p-value' in source else []) + ['Gene', 'Species', 'Region'],
['p-value'] if 'p-value' in source else []) + ['Gene', 'Species', 'Region'],
opacity=alt.condition(gene_region_selection, alt.value(0.8), alt.value(0.2))
).transform_calculate(x=f'datum[{xcol_param.name}]').properties(width=600,
height=400).interactive().add_params(
gene_region_selection, xcol_param)
).transform_calculate(x=f'datum[{xcol_param.name}]'
).properties(width=600, height=400).interactive(
).add_params(gene_region_selection, xcol_param)

st.altair_chart(chart, theme=None, use_container_width=True)


Expand Down Expand Up @@ -491,64 +491,70 @@ def BSF_page():
with stqdm(total=iteration,
desc='**:blue[Analyse sequence...] ⚠️:red[PLEASE WAIT UNTIL END WITHOUT CHANGING ANYTHING]**',
mininterval=0.1) as progress_bar:
individual_motif_occurrences = IMO.individual_motif_finder(dna_sequences, threshold, log_odds_matrix,
progress_bar,
calc_pvalue,
tss_ge_distance, alldirection)
st.session_state['individual_motif_occurrences'] = individual_motif_occurrences
individual_motif_occurrences, message = IMO.individual_motif_finder(dna_sequences, threshold,
log_odds_matrix,
progress_bar,
calc_pvalue,
tss_ge_distance, alldirection)
if message is True:
st.session_state['individual_motif_occurrences'] = individual_motif_occurrences
st.session_state['message'] = message
elif message is False:
st.error(individual_motif_occurrences)

st.divider()
if 'individual_motif_occurrences' in st.session_state:
if len(st.session_state['individual_motif_occurrences']) > 1:
current_date_time = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
st.subheader(':blue[Results]')

df = pd.DataFrame(st.session_state['individual_motif_occurrences'][1:],
columns=st.session_state['individual_motif_occurrences'][0])

df = df.sort_values(by='Rel Score', ascending=False)

st.session_state['df'] = df

st.markdown('**Table**')
tablecol1, tablecol2 = st.columns([0.75, 0.25])
with tablecol1:
st.dataframe(df, hide_index=True)
csv_file = df.to_csv(index=False)
excel_file = io.BytesIO()
df.to_excel(excel_file, index=False, sheet_name='Sheet1')
excel_file.seek(0)

with tablecol2:
st.success(f"Finding responsive elements done !")

st.markdown("")
st.markdown('**Graph**',
help='Zoom +/- with the mouse wheel. Drag while pressing the mouse to move the graph. Selection of a group by clicking on a point of the graph (double click de-selection). Double-click on a point to reset the zoom and the moving of graph.')

result_table_output(df)

with tablecol2:
st.download_button("💾 Download table (.xlsx)", excel_file,
file_name=f'Results_TFinder_{current_date_time}.xlsx',
mime="application/vnd.ms-excel", key='download-excel')
st.download_button(label="💾 Download table (.csv)", data=csv_file,
file_name=f"Results_TFinder_{current_date_time}.csv", mime="text/csv")

if st.session_state["LOCAL"] == "False":
email_receiver = st.text_input('Send results by email ✉',
value='', placeholder='Send results by email ✉',
label_visibility="collapsed")
if st.button("Send ✉"):
if jaspar == 'PWM':
if matrix_type == 'With PWM':
body = f"Hello 🧬\n\nResults obtained with TFinder.\n\nPosition Weight Matrix:\n{matrix_str}\n\nThis email also includes the sequences used in FASTA format and an Excel table of results.\n\nFor all requests/information, please refer to the 'Contact' tab on the TFinder website. We would be happy to answer all your questions.\n\nBest regards\nTFinder Team 🔎🧬"
if matrix_type == 'With FASTA sequences':
body = f"Hello 🧬\n\nResults obtained with TFinder.\n\nResponsive Elements:\n{individual_motif}\n\nPosition Weight Matrix:\n{matrix_text}\n\nThis email also includes the sequences used in FASTA format and an Excel table of results.\n\nFor all requests/information, please refer to the 'Contact' tab on the TFinder website. We would be happy to answer all your questions.\n\nBest regards\nTFinder Team 🔎🧬"
elif jaspar == 'JASPAR_ID':
body = f"Hello 🧬\n\nResults obtained with TFinder.\n\nJASPAR_ID: {jaspar_id} | Transcription Factor name: {TF_name}\n\nThis email also includes the sequences used in FASTA format and an Excel table of results.\n\nFor all requests/information, please refer to the 'Contact' tab on the TFinder website. We would be happy to answer all your questions.\n\nBest regards\nTFinder Team 🔎🧬"
else:
body = f"Hello 🧬\n\nResults obtained with TFinder.\n\nResponsive Elements:\n{IUPAC}\n\nPosition Weight Matrix:\n{matrix_text}\n\nThis email also includes the sequences used in FASTA format and an Excel table of results.\n\nFor all requests/information, please refer to the 'Contact' tab on the TFinder website. We would be happy to answer all your questions.\n\nBest regards\nTFinder Team 🔎🧬"
email(excel_file, csv_file, txt_output, email_receiver, body, jaspar)
else:
st.error(f"No consensus sequence found with the specified threshold")
try:
if 'individual_motif_occurrences' in st.session_state:
if len(st.session_state['individual_motif_occurrences']) > 0:
current_date_time = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
st.subheader(':blue[Results]')

st.markdown('**Table**')
tablecol1, tablecol2 = st.columns([0.75, 0.25])
with tablecol1:
st.dataframe(st.session_state['individual_motif_occurrences'], hide_index=True)
csv_file = st.session_state['individual_motif_occurrences'].to_csv(index=False)
excel_file = io.BytesIO()
st.session_state['individual_motif_occurrences'].to_excel(excel_file, index=False,
sheet_name='Sheet1')
excel_file.seek(0)

with tablecol2:
st.success(f"Finding responsive elements done !")

st.markdown("")
st.markdown('**Graph**',
help='Zoom +/- with the mouse wheel. Drag while pressing the mouse to move the graph. Selection of a group by clicking on a point of the graph (double click de-selection). Double-click on a point to reset the zoom and the moving of graph.')

result_table_output(st.session_state['individual_motif_occurrences'])

with tablecol2:
st.download_button("💾 Download table (.xlsx)", excel_file,
file_name=f'Results_TFinder_{current_date_time}.xlsx',
mime="application/vnd.ms-excel", key='download-excel')
st.download_button(label="💾 Download table (.csv)", data=csv_file,
file_name=f"Results_TFinder_{current_date_time}.csv", mime="text/csv")

try:
if st.session_state["LOCAL"] == "False":
email_receiver = st.text_input('Send results by email ✉',
value='', placeholder='Send results by email ✉',
label_visibility="collapsed")
if st.button("Send ✉"):
if jaspar == 'PWM':
if matrix_type == 'With PWM':
body = f"Hello 🧬\n\nResults obtained with TFinder.\n\nPosition Weight Matrix:\n{matrix_str}\n\nThis email also includes the sequences used in FASTA format and an Excel table of results.\n\nFor all requests/information, please refer to the 'Contact' tab on the TFinder website. We would be happy to answer all your questions.\n\nBest regards\nTFinder Team 🔎🧬"
if matrix_type == 'With FASTA sequences':
body = f"Hello 🧬\n\nResults obtained with TFinder.\n\nResponsive Elements:\n{individual_motif}\n\nPosition Weight Matrix:\n{matrix_text}\n\nThis email also includes the sequences used in FASTA format and an Excel table of results.\n\nFor all requests/information, please refer to the 'Contact' tab on the TFinder website. We would be happy to answer all your questions.\n\nBest regards\nTFinder Team 🔎🧬"
elif jaspar == 'JASPAR_ID':
body = f"Hello 🧬\n\nResults obtained with TFinder.\n\nJASPAR_ID: {jaspar_id} | Transcription Factor name: {TF_name}\n\nThis email also includes the sequences used in FASTA format and an Excel table of results.\n\nFor all requests/information, please refer to the 'Contact' tab on the TFinder website. We would be happy to answer all your questions.\n\nBest regards\nTFinder Team 🔎🧬"
else:
body = f"Hello 🧬\n\nResults obtained with TFinder.\n\nResponsive Elements:\n{IUPAC}\n\nPosition Weight Matrix:\n{matrix_text}\n\nThis email also includes the sequences used in FASTA format and an Excel table of results.\n\nFor all requests/information, please refer to the 'Contact' tab on the TFinder website. We would be happy to answer all your questions.\n\nBest regards\nTFinder Team 🔎🧬"
email(excel_file, csv_file, txt_output, email_receiver, body, jaspar)
except Exception:
print("You are in LOCAL")
else:
st.error(f"No consensus sequence found with the specified threshold")
except Exception as e:
print(e)
st.write(e)
5 changes: 3 additions & 2 deletions navigation/aio.py
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Original file line number Diff line number Diff line change
Expand Up @@ -103,7 +103,8 @@ def result_table_output(source):
ystop = score_range.max() + 0.02
source['Gene_Region'] = source['Gene'] + " " + source['Species'] + " " + source['Region']
source['Beginning of sequences'] = source['Position']
source['From TSS/gene end'] = source['Rel Position']
if "Rel Position" in source:
source['From TSS/gene end'] = source['Rel Position']
scale = alt.Scale(scheme='category10')
color_scale = alt.Color("Gene_Region:N", scale=scale)

Expand All @@ -113,7 +114,7 @@ def result_table_output(source):
options=['Beginning of sequences', 'From TSS/gene end'] if "Rel Position" in source else ['Beginning of sequences'],
name='(X-axis) Position from: ')

xcol_param = alt.param(value='Beginning of sequences', bind=dropdown)
xcol_param = alt.param(value='Beginning of sequences', bind=dropdown, name="x_axis")

chart = alt.Chart(source).mark_circle().encode(
x=alt.X('x:Q').title('Position (bp)'),
Expand Down
31 changes: 14 additions & 17 deletions navigation/regulatory_regions_extractor.py
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Original file line number Diff line number Diff line change
Expand Up @@ -278,17 +278,16 @@ def prom_extractor_page():
pbar.progress((i + 1) / len(data_dff),
text=f'**:blue[Extract sequence... {prom_term} **{gene_id}** from **{species}**] ⚠️:red[PLEASE WAIT UNTIL END WITHOUT CHANGING ANYTHING]**')

result_promoter_output = NCBIdna(gene_id, prom_term, upstream,
downstream).find_sequences()
result_promoter_output, message = NCBIdna(gene_id, prom_term, upstream,
downstream).find_sequences()

if not result_promoter_output.startswith('P'):
st.toast(f'{prom_term} **{gene_id}** from **{species}** extracted',
if message == "OK":
st.toast(f"{prom_term} **{gene_id}** from **{species}** extracted",
icon='🧬')
result_promoter.append(result_promoter_output)
pass

result_promoter.append(result_promoter_output)
else:
st.error(result_promoter_output)
st.error(message)
continue

else:
Expand All @@ -301,19 +300,17 @@ def prom_extractor_page():
pbar.progress((i + 1) / len(data_dff),
text=f'**:blue[Extract sequence... {prom_term} **{gene_id}** from **{species.capitalize()}**] ⚠️:red[PLEASE WAIT UNTIL END WITHOUT CHANGING ANYTHING]**')

result_promoter_output = NCBIdna(gene_id, prom_term, upstream,
downstream,
species).find_sequences()
result_promoter_output, message = NCBIdna(gene_id, prom_term, upstream,
downstream,
species).find_sequences()

if not result_promoter_output.startswith('P'):
st.toast(
f'{prom_term} **{gene_id}** from **{species.capitalize()}** extracted',
icon='🧬')
result_promoter.append(result_promoter_output)
pass
if message == "OK":
st.toast(f"{prom_term} **{gene_id}** from **{species}** extracted",
icon='🧬')

result_promoter.append(result_promoter_output)
else:
st.error(result_promoter_output)
st.error(message)
continue

result_promoter_text = "\n".join(result_promoter)
Expand Down
4 changes: 2 additions & 2 deletions requirements.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -21,7 +21,7 @@
# Old requirements:
biopython

altair~=5.4.1
altair~=5.5.0
deprecation~=2.1.0
future
hydralit_components
Expand All @@ -32,7 +32,7 @@ pandas~=2.2.2
plotly
requests~=2.32.3
stqdm~=0.0.5
streamlit~=1.34.0
streamlit~=1.40.1
streamlit_analytics
streamlit-lottie
tqdm~=4.66.4
Expand Down

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