Merge pull request #231 from dodecatheon/add-hmmer-application

Add HMMER application to Ramble

var/ramble/repos/builtin/applications/hmmer/application.py

@@ -0,0 +1,81 @@
+# Copyright 2022-2023 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 <LICENSE-APACHE or
+# https://www.apache.org/licenses/LICENSE-2.0> or the MIT license
+# <LICENSE-MIT or https://opensource.org/licenses/MIT>, at your
+# option. This file may not be copied, modified, or distributed
+# except according to those terms.
+
+import os
+from ramble.appkit import *
+from ramble.expander import Expander
+
+
+class Hmmer(SpackApplication):
+    '''HMMER is used for searching sequence databases for sequence homologs,
+    and for making sequence alignments. It implements methods using
+    probabilistic models called profile hidden Markov models (profile HMMs).
+
+    It is often used with profile databases such as Pfam (for protein
+    families), Rfam (for non-coded RNA families), Dfam (for repetitive
+    DNA based), etc.
+
+    Homepage: www.hmmer.org'''
+
+    name = 'hmmer'
+
+    maintainers('dodecatheon')
+
+    tags('molecular-dynamics', 'hidden-markov-models', 'bio-molecule')
+
+    default_compiler('gcc9', spack_spec='[email protected]')
+
+    software_spec('impi_2018', spack_spec='[email protected]')
+
+    software_spec('hmmer', spack_spec='[email protected]', compiler='gcc9')
+
+    input_file('Pfam_A',
+               url='http://ftp.ebi.ac.uk/pub/databases/Pfam/current_release/Pfam-A.hmm.gz',
+               sha256='48ec2d1123c84046b00279eae1fb3d5be1b578e6221453f329d16954c89d0d35',
+               description='The Pfam database is a large collection of protein families, ' +
+               'each represented by multiple sequence alignments and hidden Markov models (HMMs).')
+
+    input_file('uniprot_sprot_fasta',
+               url='https://ftp.uniprot.org/pub/databases/uniprot/current_release/knowledgebase/complete/uniprot_sprot.fasta.gz',
+               sha256='cab2d5a0f2bedd1923e675ccaebb5ad58c559024509e3208b074abf355d8a347',
+               description='Uniprot Swiss Prot fasta search input')
+
+    executable('execute',
+               'hmmsearch --mpi -o hmmsearch.out {database_path} {input_path}',
+               use_mpi=True)
+
+    executable('tail_hmmsearch_out',
+               'tail -100 hmmsearch.out',
+               use_mpi=False)
+
+    workload('fasta_pfam', executables=['execute', 'tail_hmmsearch_out'],
+             inputs=['Pfam_A', 'uniprot_sprot_fasta'])
+
+    workload_variable('database_path', default='{Pfam_A}/Pfam-A.hmm',
+                      description='Database path for Pfam-A',
+                      workloads=['fasta_pfam'])
+
+    workload_variable('input_path', default='{uniprot_sprot_fasta}/uniprot_sprot.fasta',
+                      description='Input path for uniprot_sprot.fasta',
+                      workloads=['fasta_pfam'])
+
+    hmmsearch_out = os.path.join(Expander.expansion_str('experiment_run_dir'),
+                                 'hmmsearch.out')
+
+    out_file = os.path.join(Expander.expansion_str('experiment_run_dir'),
+                            Expander.expansion_str('experiment_name') + '.out')
+
+    figure_of_merit('Elapsed time',
+                    fom_regex=r'# CPU.*Elapsed:\s+(?P<elapsed_time>[0-9]+:[0-9]+:[0-9]+\.*[0-9]*)\s*$',
+                    group_name='elapsed_time', log_file=out_file, units='hms')
+
+    figure_of_merit('Million dynamic programming cells per second',
+                    fom_regex=r'^#\s*Mc/sec:\s+(?P<mc_per_sec>[0-9]+)\s*',
+                    group_name='mc_per_sec', log_file=out_file, units='Mc/s')
+
+    success_criteria('ok', mode='string', match=r'^\[ok\]$', file=out_file)