v pre-1.6b

Former-commit-id: 33fafe91

 ############################################################################################
+v 1.6 beta, August 2021
+
+Aglaé Tabot joins the development team. Khodor Hannoush leaves.
+
+FEATURE CHANGES
+    - Distinct options --cmalign-opts and --cmalign-rrna-opts allow to adapt the parameters for LSU and SSU families.
+      The LSU and SSU are now aligned with Infernal options '--cpu 10 --mxsize 8192 --mxtau 0.1', which is slow, 
+      requires up to 100 GB of RAM, and yields a suboptimal alignment (tau=0.1 is quite bad), but is homogenous with the other families.
+    - The LSU and SSU therefore have defined cm_coords fields, and therefore distance matrices can be computed.
+    - We now provide for download the renumbered (standardised) 3D MMCIF files, the nucleotides being numbered by their "index_chain" in the database.
+    - We now provide for download the sequences of the 3D chains aligned by Rfam family (without Rfam sequences, which have been removed).
+    - statistics.py now computes histograms and a density estimation with Gaussian mixture models for a large set of geometric parameters, 
+      measured on the unmapped data at a given resolution threshold. The parameters include:
+        * All atom bonded distances and torsion angles
+        * Distances, flat angles and torsion angles in the Pyle/VFold model
+        * Distances, flat angles and torsion anfles in the HiRE-RNA model
+        * Sequence-dependant geometric parameters of the basepairs for all non-canonical basepairs in the HiRE-RNA model.
+      The data is saved as JSON files of parameters, and numerous figures are produced to illustrate the distributions.
+      The number of gaussians to use in the GMMs are hard-coded in geometric_stats.py after our first estimation. If you do not want to trust this estimation,
+      you can ignore it with option --rescan-nmodes. An exploration of the number of Gaussians from 1 to 8 will be performed, and the best GMM will be kept. 
+
+BUG CORRECTIONS
+    - New code file geometric_stats.py
+    - New automation script that starts from scratch
+    - Many small fixes
+    - Performance tweaks
+
+TECHNICAL CHANGES
+    - Switched to DSSR Pro.
+    - Switched to esl-alimerge instead of cmalign --merge to merge alignments.
+
+############################################################################################
 v 1.5 beta, April 2021
 
 FEATURE CHANGES

 MIT License
 
-Copyright (c) 2019 Louis Becquey
+Copyright (c) 2019-2021 IBISC, Université Paris Saclay
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

@@ -57,13 +57,14 @@ def trace_unhandled_exceptions(func):
             return func(*args, **kwargs)
         except:
             s = traceback.format_exc()
-            with open(runDir + "/errors.txt", "a") as f:
-                f.write("Exception in "+func.__name__+"\n")
-                f.write(s)
-                f.write("\n\n")
-
-            warn('Exception in '+func.__name__, error=True)
-            print(s)
+            if not "KeyboardInterrupt" in s:
+                with open(runDir + "/errors.txt", "a") as f:
+                    f.write("Exception in "+func.__name__+"\n")
+                    f.write(s)
+                    f.write("\n\n")
+
+                warn('Exception in '+func.__name__, error=True)
+                print(s)
     return wrapped_func
 
 pd.set_option('display.max_rows', None)
@@ -261,7 +262,7 @@ class Chain:
                     new_s.add(new_model)
 
             # renumber this structure (portion of the original) with the index_chain and save it in a cif file
-            t=pdb.Structure.Structure(new_s.get_id())
+            t = pdb.Structure.Structure(new_s.get_id())
             for model in new_s:
                 new_model_t=pdb.Model.Model(model.get_id())
                 for chain in model:
@@ -288,7 +289,7 @@ class Chain:
                         # particular case 6n5s_1_A, residue 201 in the original cif file (resname = G and HETATM = H_G)
                         if nt == 'A' or (nt == 'G' and (self.chain_label != '6n5s_1_A' or resseq != 201)) or nt == 'C' or nt == 'U' or nt in ['DG', 'DU', 'DC', 'DA', 'DI', 'DT' ] or nt == 'N' or nt == 'I' :
                             res=chain[(' ', resseq, icode_res)]
-                        else : #modified nucleotides (e.g. chain 5l4o_1_A)
+                        else : # modified nucleotides (e.g. chain 5l4o_1_A)
                             het='H_' + nt
                             res=chain[(het, resseq, icode_res)]
                         res_id=res.get_id()
@@ -1599,7 +1600,7 @@ class Pipeline:
         try:
             fam_pbar = tqdm(total=len(self.fam_list), desc="RNA families", position=0, leave=True)
             # Apply work_pssm_remap to each RNA family
-            for i, _ in enumerate(p.imap_unordered(work_pssm_remap, self.fam_list, chunksize=1)):
+            for i, _ in enumerate(p.imap_unordered(partial(work_pssm_remap, useSina=pp.USESINA), self.fam_list, chunksize=1)):
                 # Everytime the iteration finishes on a family, update the global progress bar over the RNA families
                 fam_pbar.update(1)
             fam_pbar.close()
@@ -1654,7 +1655,7 @@ class Pipeline:
         p = Pool(initializer=init_with_tqdm, initargs=(tqdm.get_lock(),), processes=3)
         try:
             pbar = tqdm(total=len(self.loaded_chains), desc="Saving chains to CSV", position=0, leave=True)
-            for _, _2 in enumerate(p.imap_unordered(work_save, self.loaded_chains)):
+            for _, _2 in enumerate(p.imap_unordered(partial(work_save, homology=pp.HOMOLOGY), self.loaded_chains)):
                 pbar.update(1)
             pbar.close()
             p.close()
@@ -1700,18 +1701,28 @@ class Pipeline:
         if self.ARCHIVE:
             os.makedirs(runDir + "/archive", exist_ok=True)
             datestr = time.strftime('%Y%m%d')
+
+            # The text files
             subprocess.run(["rm", "-f", runDir + f"/archive/RNANET_datapoints_latest.tar.gz"])
             subprocess.run(["tar", "-C", path_to_3D_data + "/datapoints", "-czf", runDir + f"/archive/RNANET_datapoints_{datestr}.tar.gz", "."])
             subprocess.run(["ln", "-s", runDir + f"/archive/RNANET_datapoints_{datestr}.tar.gz", runDir + f"/archive/RNANET_datapoints_latest.tar.gz"])
 
+            # The alignments
             if self.HOMOLOGY:
-                # gather the alignments
                 os.makedirs(path_to_seq_data + "realigned/3d_only", exist_ok=True)
                 for f in os.listdir(path_to_seq_data + "realigned"):
                     if "3d_only.afa" in f:
                         subprocess.run(["cp", path_to_seq_data + "realigned/" + f, path_to_seq_data + "realigned/3d_only"])
-                subprocess.run(["rm", "-f", runDir + f"/archive/RNANET_alignments_latest.tar.gz"])
-                subprocess.run(["tar", "-C", path_to_seq_data + "realigned/3d_only" , "-czf", runDir + f"/archive/RNANET_alignments_latest.tar.gz", "."])
+                subprocess.run(["rm", "-f", runDir + f"/archive/RNANET_3dOnlyAlignments_latest.tar.gz"])
+                subprocess.run(["tar", "-C", path_to_seq_data + "realigned/3d_only" , "-czf", runDir + f"/archive/RNANET_3dOnlyAlignments_latest.tar.gz", "."])
+
+            # The 3D files
+            if os.path.isdir(path_to_3D_data + "rna_mapped_to_Rfam"):
+                subprocess.run(["rm", "-f", runDir + f"/archive/RNANET_MMCIFmappedToRfam_latest.tar.gz"])
+                subprocess.run(["tar", "-C", path_to_3D_data + "rna_mapped_to_Rfam" , "-czf", runDir + f"/archive/RNANET_MMCIFmappedToRfam_latest.tar.gz", "."])
+            if os.path.isdir(path_to_3D_data + "rna_only"):
+                subprocess.run(["rm", "-f", runDir + f"/archive/RNANET_MMCIFall_latest.tar.gz"])
+                subprocess.run(["tar", "-C", path_to_3D_data + "rna_only" , "-czf", runDir + f"/archive/RNANET_MMCIFall_latest.tar.gz", "."])
 
     def sanitize_database(self):
         """Searches for issues in the database and correct them"""
@@ -1813,7 +1824,7 @@ def warn(message, error=False):
     """
     # Cut if too long
     if len(message) > 66:
-        x = message.find(' ', 50, 66)
+        x = message.find(' ', 40, 66)
         if x != -1:
             warn(message[:x], error=error)
             warn(message[x+1:], error=error)
@@ -2809,7 +2820,7 @@ def work_save_pydca(f,alignment):
             warn(e)
 
 @trace_unhandled_exceptions
-def work_pssm_remap(f):
+def work_pssm_remap(f, useSina=False):
     """Computes Position-Specific-Scoring-Matrices given the multiple sequence alignment of the RNA family.
     This also remaps the 3D object sequence with the aligned sequence in the MSA.
     If asked, the 3D object sequence is completed by the consensus nucleotide when one of them is missing.
@@ -2991,7 +3002,7 @@ def work_pssm_remap(f):
     setproctitle(f"RNAnet.py work_pssm_remap({f}) insert/match states")
 
     # Get back the information of match/insertion states from the STK file
-    if (not use_sina) or (f not in SSU_set and f not in LSU_set):
+    if (not useSina) or (f not in SSU_set and f not in LSU_set):
         alignstk = AlignIO.read(path_to_seq_data + "realigned/" + f + "++.stk", "stockholm")
         consensus_2d = alignstk.column_annotations["secondary_structure"]
         del alignstk
@@ -3037,8 +3048,6 @@ def work_pssm_remap(f):
                           gap_percent, consensus, cons_sec_struct)
                           VALUES (?, 0, 0, NULL, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, '-', NULL);""", data=(f,))
     
-    
-    
     # Save the number of "used columns" to table family ( = the length of the alignment if it was composed only of the RNANet chains)
     sql_execute(conn, f"UPDATE family SET ali_filtered_len = ? WHERE rfam_acc = ?;", data=(len(columns_to_save), f))
     conn.close()
@@ -3171,15 +3180,9 @@ if __name__ == "__main__":
         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:
+    if pp.HOMOLOGY and 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.")
-
     # At this point, structure, chain and nucleotide tables of the database are up to date.
     # (Modulo some statistics computed by statistics.py)
 
@@ -3187,33 +3190,34 @@ if __name__ == "__main__":
     # Homology information
     # ===========================================================================
 
-    if pp.SELECT_ONLY is None:
-        # If your job failed, you can comment all the "3D information" part and start from here.
-        pp.checkpoint_load_chains()
+    if pp.HOMOLOGY:
+        if pp.SELECT_ONLY is None:
+            # If your job failed, you can comment all the "3D information" part and start from here.
+            pp.checkpoint_load_chains()
 
-    # Get the list of Rfam families found in the update
-    rfam_acc_to_download = {}
-    for c in pp.loaded_chains:
-        if c.mapping.rfam_acc not in rfam_acc_to_download.keys():
-            rfam_acc_to_download[c.mapping.rfam_acc] = [c]
-        else:
-            rfam_acc_to_download[c.mapping.rfam_acc].append(c)
+        # Get the list of Rfam families found in the update
+        rfam_acc_to_download = {}
+        for c in pp.loaded_chains:
+            if c.mapping.rfam_acc not in rfam_acc_to_download.keys():
+                rfam_acc_to_download[c.mapping.rfam_acc] = [c]
+            else:
+                rfam_acc_to_download[c.mapping.rfam_acc].append(c)
 
-    print(f"> Identified {len(rfam_acc_to_download.keys())} families to update and re-align with the crystals' sequences")
-    pp.fam_list = sorted(rfam_acc_to_download.keys())
+        print(f"> Identified {len(rfam_acc_to_download.keys())} families to update and re-align with the crystals' sequences")
+        pp.fam_list = sorted(rfam_acc_to_download.keys())
 
-    if len(pp.fam_list):
-        pp.prepare_sequences()
-        pp.realign()
+        if len(pp.fam_list):
+            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)
+            # At this point, the family table is almost up to date 
+            # (lacking idty_percent and ali_filtered_length, both set in statistics.py)
 
-        thr_idx_mgr = Manager()
-        idxQueue = thr_idx_mgr.Queue()
+            thr_idx_mgr = Manager()
+            idxQueue = thr_idx_mgr.Queue()
 
-        pp.remap()
-        pp.extractCMs()
+            pp.remap()
+            pp.extractCMs()
 
     # At this point, the align_column and re_mapping tables are up-to-date.
 

@@ -35,7 +35,7 @@ nohup bash -c 'time docker run --rm -v /path/to/3D/data/folder:/3D -v /path/to/s
 # Method 2 : Classical command line installation (Linux only)
 
 You need to install the dependencies:
-- DSSR 1.9.9 or newer, you need to register to the X3DNA forum [here](http://forum.x3dna.org/site-announcements/download-instructions/) and then download the DSSR binary [on that page](http://forum.x3dna.org/downloads/3dna-download/).  Make sure to have the `x3dna-dssr` binary in your $PATH variable so that RNANet.py finds it.
+- DSSR 1.9.9 or newer, you need to register to ask for a DSSR (academic) license [on that page](http://innovation.columbia.edu/technologies/CU20391). Make sure to have the `x3dna-dssr` binary in your $PATH variable so that RNANet.py finds it.
 - Infernal 1.1.4 or newer, to download at [Eddylab](http://eddylab.org/infernal/), several options are available depending on your preferences. Make sure to have the `cmalign`, `cmfetch`, `cmbuild`, `esl-alimanip`, `esl-alimerge`, `esl-alipid` and `esl-reformat` binaries in your $PATH variable, so that RNANet.py can find them.
 - SINA (if you plan to use it), follow [these instructions](https://sina.readthedocs.io/en/latest/install.html) for example. Make sure to have the `sina` binary in your $PATH.
 - Sqlite 3, available under the name *sqlite* in every distro's package manager,

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