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Louis BECQUEY
/
RNANet
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Authored by
Louis BECQUEY
2021-01-30 01:22:28 +0100
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edde38ec008d6ad15f48a0152ada0c80d5361665
edde38ec
1 parent
e74c6fe3
v1.3 beta uncommented
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37 deletions
RNAnet.py
RNAnet.py
View file @
edde38e
...
...
@@ -2601,45 +2601,45 @@ if __name__ == "__main__":
# compute an update compared to what is in the table "chain" (comparison on structure_id + chain_name + rfam_acc).
# If --all was passed, all the structures are kept.
# Fills pp.update with Chain() objects.
#
pp.list_available_mappings()
pp
.
list_available_mappings
()
# ===========================================================================
# 3D information
# ===========================================================================
#
#
Download and annotate new RNA 3D chains (Chain objects in pp.update)
#
#
If the original cif file and/or the Json DSSR annotation file already exist, they are not redownloaded/recomputed.
#
#
pp.dl_and_annotate(coeff_ncores=0.5)
#
pp.dl_and_annotate(coeff_ncores=1.0)
#
print("Here we go.")
#
#
At this point, the structure table is up to date.
#
#
Now save the DSSR annotations to the database.
#
#
Extract the 3D chains to separate structure files if asked with --extract.
#
pp.build_chains(coeff_ncores=1.0)
#
if len(pp.to_retry):
#
# Redownload and re-annotate
#
print("> Retrying to annotate some structures which just failed.", flush=True)
#
pp.dl_and_annotate(retry=True, coeff_ncores=0.3) #
#
pp.build_chains(retry=True, coeff_ncores=1.0) # Use half the cores to reduce required amount of memory
#
print(f"> Loaded {len(pp.loaded_chains)} RNA chains ({len(pp.update) - len(pp.loaded_chains)} ignored/errors).")
#
if len(no_nts_set):
#
print(f"Among errors, {len(no_nts_set)} structures seem to contain RNA chains without defined nucleotides:", no_nts_set, flush=True)
#
if len(weird_mappings):
#
print(f"{len(weird_mappings)} mappings to Rfam were taken as absolute positions instead of residue numbers:", weird_mappings, flush=True)
#
if pp.SELECT_ONLY is None:
#
pp.checkpoint_save_chains()
#
if not pp.HOMOLOGY:
#
# Save chains to file
#
for c in pp.loaded_chains:
#
work_save(c, homology=False)
#
print("Completed.")
#
exit(0)
#
#
At this point, structure, chain and nucleotide tables of the database are up to date.
#
#
(Modulo some statistics computed by statistics.py)
# Download and annotate new RNA 3D chains (Chain objects in pp.update)
# If the original cif file and/or the Json DSSR annotation file already exist, they are not redownloaded/recomputed.
# pp.dl_and_annotate(coeff_ncores=0.5)
pp
.
dl_and_annotate
(
coeff_ncores
=
1.0
)
print
(
"Here we go."
)
# At this point, the structure table is up to date.
# Now save the DSSR annotations to the database.
# Extract the 3D chains to separate structure files if asked with --extract.
pp
.
build_chains
(
coeff_ncores
=
1.0
)
if
len
(
pp
.
to_retry
):
# Redownload and re-annotate
print
(
"> Retrying to annotate some structures which just failed."
,
flush
=
True
)
pp
.
dl_and_annotate
(
retry
=
True
,
coeff_ncores
=
0.3
)
#
pp
.
build_chains
(
retry
=
True
,
coeff_ncores
=
1.0
)
# Use half the cores to reduce required amount of memory
print
(
f
"> Loaded {len(pp.loaded_chains)} RNA chains ({len(pp.update) - len(pp.loaded_chains)} ignored/errors)."
)
if
len
(
no_nts_set
):
print
(
f
"Among errors, {len(no_nts_set)} structures seem to contain RNA chains without defined nucleotides:"
,
no_nts_set
,
flush
=
True
)
if
len
(
weird_mappings
):
print
(
f
"{len(weird_mappings)} mappings to Rfam were taken as absolute positions instead of residue numbers:"
,
weird_mappings
,
flush
=
True
)
if
pp
.
SELECT_ONLY
is
None
:
pp
.
checkpoint_save_chains
()
if
not
pp
.
HOMOLOGY
:
# Save chains to file
for
c
in
pp
.
loaded_chains
:
work_save
(
c
,
homology
=
False
)
print
(
"Completed."
)
exit
(
0
)
# At this point, structure, chain and nucleotide tables of the database are up to date.
# (Modulo some statistics computed by statistics.py)
# ===========================================================================
# Homology information
...
...
@@ -2661,8 +2661,8 @@ if __name__ == "__main__":
pp
.
fam_list
=
sorted
(
rfam_acc_to_download
.
keys
())
if
len
(
pp
.
fam_list
):
#
pp.prepare_sequences()
#
pp.realign()
pp
.
prepare_sequences
()
pp
.
realign
()
# At this point, the family table is almost up to date
# (lacking idty_percent and ali_filtered_length, both set in statistics.py)
...
...
@@ -2678,7 +2678,7 @@ if __name__ == "__main__":
# Prepare the results
# ==========================================================================================
#
pp.sanitize_database()
pp
.
sanitize_database
()
pp
.
output_results
()
print
(
"Completed."
)
# This part of the code is supposed to release some serotonin in the modeller's brain, do not remove
...
...
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