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@@ -0,0 +1 @@ +/pyhmmer-0.7.3.tar.gz diff --git a/python-pyhmmer.spec b/python-pyhmmer.spec new file mode 100644 index 0000000..fc087fc --- /dev/null +++ b/python-pyhmmer.spec @@ -0,0 +1,664 @@ +%global _empty_manifest_terminate_build 0 +Name: python-pyhmmer +Version: 0.7.3 +Release: 1 +Summary: Cython bindings and Python interface to HMMER3. +License: MIT +URL: https://github.com/althonos/pyhmmer +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/63/6c/9ba4ec4440099d30c4821e8740edb2340e6192b934e81057f7921666c1db/pyhmmer-0.7.3.tar.gz +BuildArch: noarch + +Requires: python3-psutil + +%description +# ππ‘β¦οΈπ¦ PyHMMER [](https://github.com/althonos/pyhmmer/stargazers) + +*[Cython](https://cython.org/) bindings and Python interface to [HMMER3](http://hmmer.org/).* + +[](https://github.com/althonos/pyhmmer/actions) +[](https://codecov.io/gh/althonos/pyhmmer/) +[](https://pypi.org/project/pyhmmer) +[](https://anaconda.org/bioconda/pyhmmer) +[](https://aur.archlinux.org/packages/python-pyhmmer) +[](https://pypi.org/project/pyhmmer/#files) +[](https://pypi.org/project/pyhmmer/#files) +[](https://pypi.org/project/pyhmmer/#files) +[](https://choosealicense.com/licenses/mit/) +[](https://github.com/althonos/pyhmmer/) +[](https://git.embl.de/larralde/pyhmmer/) +[](https://github.com/althonos/pyhmmer/issues) +[](https://pyhmmer.readthedocs.io) +[](https://github.com/althonos/pyhmmer/blob/master/CHANGELOG.md) +[](https://pepy.tech/project/pyhmmer) +[](https://doi.org/10.5281/zenodo.4270012) + + +## πΊοΈ Overview + +HMMER is a biological sequence analysis tool that uses profile hidden Markov +models to search for sequence homologs. HMMER3 is developed and maintained by +the [Eddy/Rivas Laboratory](http://eddylab.org/) at Harvard University. + +`pyhmmer` is a Python package, implemented using the [Cython](https://cython.org/) +language, that provides bindings to HMMER3. It directly interacts with the +HMMER internals, which has the following advantages over CLI wrappers +(like [`hmmer-py`](https://pypi.org/project/hmmer/)): + +- **single dependency**: If your software or your analysis pipeline is + distributed as a Python package, you can add `pyhmmer` as a dependency to + your project, and stop worrying about the HMMER binaries being properly + setup on the end-user machine. +- **no intermediate files**: Everything happens in memory, in Python objects + you have control on, making it easier to pass your inputs to HMMER without + needing to write them to a temporary file. Output retrieval is also done + in memory, via instances of the + [`pyhmmer.plan7.TopHits`](https://pyhmmer.readthedocs.io/en/stable/api/plan7.html#pyhmmer.plan7.TopHits) + class. +- **no input formatting**: The Easel object model is exposed in the + [`pyhmmer.easel`](https://pyhmmer.readthedocs.io/en/stable/api/easel.html) + module, and you have the possibility to build a + [`DigitalSequence`](https://pyhmmer.readthedocs.io/en/stable/api/easel.html#pyhmmer.easel.DigitalSequence) + object yourself to pass to the HMMER pipeline. This is useful if your sequences are already + loaded in memory, for instance because you obtained them from another + Python library (such as [Pyrodigal](https://github.com/althonos/pyrodigal) + or [Biopython](https://biopython.org/)). +- **no output formatting**: HMMER3 is notorious for its numerous output files + and its fixed-width tabular output, which is hard to parse (even + [`Bio.SearchIO.HmmerIO`](https://biopython.org/docs/dev/api/Bio.SearchIO.HmmerIO.html) + is struggling on some sequences). +- **efficient**: Using `pyhmmer` to launch `hmmsearch` on sequences + and HMMs in disk storage is typically as fast as directly using the + `hmmsearch` binary (see the [Benchmarks section](#%EF%B8%8F-benchmarks)). + [`pyhmmer.hmmer.hmmsearch`](https://pyhmmer.readthedocs.io/en/stable/api/hmmer.html#hmmsearch) + uses a different parallelisation strategy compared to + the `hmmsearch` binary from HMMER, which can help getting the most of + multiple CPUs when annotating smaller sequence databases. + +*This library is still a work-in-progress, and in an experimental stage, +but it should already pack enough features to run biological analyses or +workflows involving `hmmsearch`, `hmmscan`, `nhmmer`, `phmmer`, `hmmbuild` +and `hmmalign`.* + + +## π§ Installing + +`pyhmmer` can be installed from [PyPI](https://pypi.org/project/pyhmmer/), +which hosts some pre-built CPython wheels for x86-64 Linux, as well as the +code required to compile from source with Cython: +```console +$ pip install pyhmmer +``` + +Compilation for UNIX PowerPC is not tested in CI, but should work out of the +box. Other architectures (e.g. Arm) and OSes (e.g. Windows) are not +supported by HMMER. + +A [Bioconda](https://bioconda.github.io/) package is also available: +```console +$ conda install -c bioconda pyhmmer +``` + + +## π Documentation + +A complete [API reference](https://pyhmmer.readthedocs.io/en/stable/api/) can +be found in the [online documentation](https://pyhmmer.readthedocs.io/), or +directly from the command line using +[`pydoc`](https://docs.python.org/3/library/pydoc.html): +```console +$ pydoc pyhmmer.easel +$ pydoc pyhmmer.plan7 +``` + + +## π‘ Example + +Use `pyhmmer` to run `hmmsearch` to search for Type 2 PKS domains +([`t2pks.hmm`](https://raw.githubusercontent.com/althonos/pyhmmer/master/pyhmmer/tests/data/hmms/txt/t2pks.hmm)) +inside proteins extracted from the genome of *Anaerococcus provencensis* +([`938293.PRJEB85.HG003687.faa`](https://raw.githubusercontent.com/althonos/pyhmmer/master/pyhmmer/tests/data/seqs/938293.PRJEB85.HG003687.faa)). +This will produce an iterable over +[`TopHits`] that can be used for further sorting/querying in Python. +Processing happens in parallel using Python threads, and a [`TopHits`] +object is yielded for every [`HMM`] passed in the input iterable. + +[`HMM`]: https://pyhmmer.readthedocs.io/en/stable/api/plan7.html#pyhmmer.plan7.HMM +[`TopHits`]: https://pyhmmer.readthedocs.io/en/stable/api/plan7.html#pyhmmer.plan7.TopHits + +```python +import pyhmmer + +with pyhmmer.easel.SequenceFile("pyhmmer/tests/data/seqs/938293.PRJEB85.HG003687.faa", digital=True) as seq_file: + sequences = list(seq_file) + +with pyhmmer.plan7.HMMFile("pyhmmer/tests/data/hmms/txt/t2pks.hmm") as hmm_file: + for hits in pyhmmer.hmmsearch(hmm_file, sequences, cpus=4): + print(f"HMM {hits.query_name.decode()} found {len(hits)} hits in the target sequences") +``` + +Have a look at more in-depth examples such as [building a HMM from an alignment](https://pyhmmer.readthedocs.io/en/stable/examples/msa_to_hmm.html), +[analysing the active site of a hit](https://pyhmmer.readthedocs.io/en/stable/examples/active_site.html), +or [fetching marker genes from a genome](https://pyhmmer.readthedocs.io/en/stable/examples/fetchmgs.html) +in the [Examples](https://pyhmmer.readthedocs.io/en/stable/examples/index.html) +page of the [online documentation](https://pyhmmer.readthedocs.io/). + + +## π Feedback + +### β οΈ Issue Tracker + +Found a bug ? Have an enhancement request ? Head over to the [GitHub issue +tracker](https://github.com/althonos/pyhmmer/issues) if you need to report +or ask something. If you are filing in on a bug, please include as much +information as you can about the issue, and try to recreate the same bug +in a simple, easily reproducible situation. + +### ποΈ Contributing + +Contributions are more than welcome! See [`CONTRIBUTING.md`](https://github.com/althonos/pyhmmer/blob/master/CONTRIBUTING.md) for more details. + + +## β±οΈ Benchmarks + +Benchmarks were run on a [i7-10710U CPU](https://ark.intel.com/content/www/us/en/ark/products/196448/intel-core-i7-10710u-processor-12m-cache-up-to-4-70-ghz.html) running @1.10GHz with 6 physical / 12 +logical cores, using a FASTA file containing 4,489 protein sequences extracted +from the genome of *Escherichia coli* +([`562.PRJEB4685`](https://progenomes.embl.de/genome.cgi)) +and the version 33.1 of the [Pfam](https://pfam.xfam.org/) HMM library containing +18,259 domains. Commands were run 3 times on a warm SSD. *Plain lines show +the times for pressed HMMs, and dashed-lines the times for HMMs in text format.* + + + +Raw numbers can be found in the [`benches` folder](https://github.com/althonos/pyhmmer/blob/master/benches/). +They suggest that `phmmer` should be run with the number of *logical* cores, +while `hmmsearch` should be run with the number of *physical* cores (or less). +A possible explanation for this observation would be that HMMER +platform-specific code requires too many [SIMD](https://en.wikipedia.org/wiki/SIMD) +registers per thread to benefit from [simultaneous multi-threading](https://en.wikipedia.org/wiki/Simultaneous_multithreading). + +To read more about how PyHMMER achieves better parallelism than HMMER for +many-to-many searches, have a look at the [Performance page](https://pyhmmer.readthedocs.io/en/stable/performance.html) +of the documentation. + + +## π See Also + +Building a HMM from scratch? Then you may be interested in the [`pyfamsa`](https://pypi.org/project/pyfamsa/) +package, providing bindings to [FAMSA](https://github.com/refresh-bio/FAMSA), +a very fast multiple sequence aligner. In addition, you may want to trim alignments: +in that case, consider [`pytrimal`](https://pypi.org/project/pytrimal), which +wraps [trimAl 2.0](https://github.com/inab/trimal/tree/2.0_RC). + +If despite of all the advantages listed earlier, you would rather use HMMER +through its CLI, this package will not be of great help. You can instead check +the [`hmmer-py`](https://github.com/EBI-Metagenomics/hmmer-py) package developed +by [Danilo Horta](https://github.com/horta) at the [EMBL-EBI](https://www.ebi.ac.uk). + + +## βοΈ License + +This library is provided under the [MIT License](https://choosealicense.com/licenses/mit/). +The HMMER3 and Easel code is available under the +[BSD 3-clause](https://choosealicense.com/licenses/bsd-3-clause/) license. +See `vendor/hmmer/LICENSE` and `vendor/easel/LICENSE` for more information. + +*This project is in no way affiliated, sponsored, or otherwise endorsed by +the [original HMMER authors](http://hmmer.org/). It was developed by +[Martin Larralde](https://github.com/althonos/pyhmmer) during his PhD project +at the [European Molecular Biology Laboratory](https://www.embl.de/) in +the [Zeller team](https://github.com/zellerlab).* + + +%package -n python3-pyhmmer +Summary: Cython bindings and Python interface to HMMER3. +Provides: python-pyhmmer +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-pyhmmer +# ππ‘β¦οΈπ¦ PyHMMER [](https://github.com/althonos/pyhmmer/stargazers) + +*[Cython](https://cython.org/) bindings and Python interface to [HMMER3](http://hmmer.org/).* + +[](https://github.com/althonos/pyhmmer/actions) +[](https://codecov.io/gh/althonos/pyhmmer/) +[](https://pypi.org/project/pyhmmer) +[](https://anaconda.org/bioconda/pyhmmer) +[](https://aur.archlinux.org/packages/python-pyhmmer) +[](https://pypi.org/project/pyhmmer/#files) +[](https://pypi.org/project/pyhmmer/#files) +[](https://pypi.org/project/pyhmmer/#files) +[](https://choosealicense.com/licenses/mit/) +[](https://github.com/althonos/pyhmmer/) +[](https://git.embl.de/larralde/pyhmmer/) +[](https://github.com/althonos/pyhmmer/issues) +[](https://pyhmmer.readthedocs.io) +[](https://github.com/althonos/pyhmmer/blob/master/CHANGELOG.md) +[](https://pepy.tech/project/pyhmmer) +[](https://doi.org/10.5281/zenodo.4270012) + + +## πΊοΈ Overview + +HMMER is a biological sequence analysis tool that uses profile hidden Markov +models to search for sequence homologs. HMMER3 is developed and maintained by +the [Eddy/Rivas Laboratory](http://eddylab.org/) at Harvard University. + +`pyhmmer` is a Python package, implemented using the [Cython](https://cython.org/) +language, that provides bindings to HMMER3. It directly interacts with the +HMMER internals, which has the following advantages over CLI wrappers +(like [`hmmer-py`](https://pypi.org/project/hmmer/)): + +- **single dependency**: If your software or your analysis pipeline is + distributed as a Python package, you can add `pyhmmer` as a dependency to + your project, and stop worrying about the HMMER binaries being properly + setup on the end-user machine. +- **no intermediate files**: Everything happens in memory, in Python objects + you have control on, making it easier to pass your inputs to HMMER without + needing to write them to a temporary file. Output retrieval is also done + in memory, via instances of the + [`pyhmmer.plan7.TopHits`](https://pyhmmer.readthedocs.io/en/stable/api/plan7.html#pyhmmer.plan7.TopHits) + class. +- **no input formatting**: The Easel object model is exposed in the + [`pyhmmer.easel`](https://pyhmmer.readthedocs.io/en/stable/api/easel.html) + module, and you have the possibility to build a + [`DigitalSequence`](https://pyhmmer.readthedocs.io/en/stable/api/easel.html#pyhmmer.easel.DigitalSequence) + object yourself to pass to the HMMER pipeline. This is useful if your sequences are already + loaded in memory, for instance because you obtained them from another + Python library (such as [Pyrodigal](https://github.com/althonos/pyrodigal) + or [Biopython](https://biopython.org/)). +- **no output formatting**: HMMER3 is notorious for its numerous output files + and its fixed-width tabular output, which is hard to parse (even + [`Bio.SearchIO.HmmerIO`](https://biopython.org/docs/dev/api/Bio.SearchIO.HmmerIO.html) + is struggling on some sequences). +- **efficient**: Using `pyhmmer` to launch `hmmsearch` on sequences + and HMMs in disk storage is typically as fast as directly using the + `hmmsearch` binary (see the [Benchmarks section](#%EF%B8%8F-benchmarks)). + [`pyhmmer.hmmer.hmmsearch`](https://pyhmmer.readthedocs.io/en/stable/api/hmmer.html#hmmsearch) + uses a different parallelisation strategy compared to + the `hmmsearch` binary from HMMER, which can help getting the most of + multiple CPUs when annotating smaller sequence databases. + +*This library is still a work-in-progress, and in an experimental stage, +but it should already pack enough features to run biological analyses or +workflows involving `hmmsearch`, `hmmscan`, `nhmmer`, `phmmer`, `hmmbuild` +and `hmmalign`.* + + +## π§ Installing + +`pyhmmer` can be installed from [PyPI](https://pypi.org/project/pyhmmer/), +which hosts some pre-built CPython wheels for x86-64 Linux, as well as the +code required to compile from source with Cython: +```console +$ pip install pyhmmer +``` + +Compilation for UNIX PowerPC is not tested in CI, but should work out of the +box. Other architectures (e.g. Arm) and OSes (e.g. Windows) are not +supported by HMMER. + +A [Bioconda](https://bioconda.github.io/) package is also available: +```console +$ conda install -c bioconda pyhmmer +``` + + +## π Documentation + +A complete [API reference](https://pyhmmer.readthedocs.io/en/stable/api/) can +be found in the [online documentation](https://pyhmmer.readthedocs.io/), or +directly from the command line using +[`pydoc`](https://docs.python.org/3/library/pydoc.html): +```console +$ pydoc pyhmmer.easel +$ pydoc pyhmmer.plan7 +``` + + +## π‘ Example + +Use `pyhmmer` to run `hmmsearch` to search for Type 2 PKS domains +([`t2pks.hmm`](https://raw.githubusercontent.com/althonos/pyhmmer/master/pyhmmer/tests/data/hmms/txt/t2pks.hmm)) +inside proteins extracted from the genome of *Anaerococcus provencensis* +([`938293.PRJEB85.HG003687.faa`](https://raw.githubusercontent.com/althonos/pyhmmer/master/pyhmmer/tests/data/seqs/938293.PRJEB85.HG003687.faa)). +This will produce an iterable over +[`TopHits`] that can be used for further sorting/querying in Python. +Processing happens in parallel using Python threads, and a [`TopHits`] +object is yielded for every [`HMM`] passed in the input iterable. + +[`HMM`]: https://pyhmmer.readthedocs.io/en/stable/api/plan7.html#pyhmmer.plan7.HMM +[`TopHits`]: https://pyhmmer.readthedocs.io/en/stable/api/plan7.html#pyhmmer.plan7.TopHits + +```python +import pyhmmer + +with pyhmmer.easel.SequenceFile("pyhmmer/tests/data/seqs/938293.PRJEB85.HG003687.faa", digital=True) as seq_file: + sequences = list(seq_file) + +with pyhmmer.plan7.HMMFile("pyhmmer/tests/data/hmms/txt/t2pks.hmm") as hmm_file: + for hits in pyhmmer.hmmsearch(hmm_file, sequences, cpus=4): + print(f"HMM {hits.query_name.decode()} found {len(hits)} hits in the target sequences") +``` + +Have a look at more in-depth examples such as [building a HMM from an alignment](https://pyhmmer.readthedocs.io/en/stable/examples/msa_to_hmm.html), +[analysing the active site of a hit](https://pyhmmer.readthedocs.io/en/stable/examples/active_site.html), +or [fetching marker genes from a genome](https://pyhmmer.readthedocs.io/en/stable/examples/fetchmgs.html) +in the [Examples](https://pyhmmer.readthedocs.io/en/stable/examples/index.html) +page of the [online documentation](https://pyhmmer.readthedocs.io/). + + +## π Feedback + +### β οΈ Issue Tracker + +Found a bug ? Have an enhancement request ? Head over to the [GitHub issue +tracker](https://github.com/althonos/pyhmmer/issues) if you need to report +or ask something. If you are filing in on a bug, please include as much +information as you can about the issue, and try to recreate the same bug +in a simple, easily reproducible situation. + +### ποΈ Contributing + +Contributions are more than welcome! See [`CONTRIBUTING.md`](https://github.com/althonos/pyhmmer/blob/master/CONTRIBUTING.md) for more details. + + +## β±οΈ Benchmarks + +Benchmarks were run on a [i7-10710U CPU](https://ark.intel.com/content/www/us/en/ark/products/196448/intel-core-i7-10710u-processor-12m-cache-up-to-4-70-ghz.html) running @1.10GHz with 6 physical / 12 +logical cores, using a FASTA file containing 4,489 protein sequences extracted +from the genome of *Escherichia coli* +([`562.PRJEB4685`](https://progenomes.embl.de/genome.cgi)) +and the version 33.1 of the [Pfam](https://pfam.xfam.org/) HMM library containing +18,259 domains. Commands were run 3 times on a warm SSD. *Plain lines show +the times for pressed HMMs, and dashed-lines the times for HMMs in text format.* + + + +Raw numbers can be found in the [`benches` folder](https://github.com/althonos/pyhmmer/blob/master/benches/). +They suggest that `phmmer` should be run with the number of *logical* cores, +while `hmmsearch` should be run with the number of *physical* cores (or less). +A possible explanation for this observation would be that HMMER +platform-specific code requires too many [SIMD](https://en.wikipedia.org/wiki/SIMD) +registers per thread to benefit from [simultaneous multi-threading](https://en.wikipedia.org/wiki/Simultaneous_multithreading). + +To read more about how PyHMMER achieves better parallelism than HMMER for +many-to-many searches, have a look at the [Performance page](https://pyhmmer.readthedocs.io/en/stable/performance.html) +of the documentation. + + +## π See Also + +Building a HMM from scratch? Then you may be interested in the [`pyfamsa`](https://pypi.org/project/pyfamsa/) +package, providing bindings to [FAMSA](https://github.com/refresh-bio/FAMSA), +a very fast multiple sequence aligner. In addition, you may want to trim alignments: +in that case, consider [`pytrimal`](https://pypi.org/project/pytrimal), which +wraps [trimAl 2.0](https://github.com/inab/trimal/tree/2.0_RC). + +If despite of all the advantages listed earlier, you would rather use HMMER +through its CLI, this package will not be of great help. You can instead check +the [`hmmer-py`](https://github.com/EBI-Metagenomics/hmmer-py) package developed +by [Danilo Horta](https://github.com/horta) at the [EMBL-EBI](https://www.ebi.ac.uk). + + +## βοΈ License + +This library is provided under the [MIT License](https://choosealicense.com/licenses/mit/). +The HMMER3 and Easel code is available under the +[BSD 3-clause](https://choosealicense.com/licenses/bsd-3-clause/) license. +See `vendor/hmmer/LICENSE` and `vendor/easel/LICENSE` for more information. + +*This project is in no way affiliated, sponsored, or otherwise endorsed by +the [original HMMER authors](http://hmmer.org/). It was developed by +[Martin Larralde](https://github.com/althonos/pyhmmer) during his PhD project +at the [European Molecular Biology Laboratory](https://www.embl.de/) in +the [Zeller team](https://github.com/zellerlab).* + + +%package help +Summary: Development documents and examples for pyhmmer +Provides: python3-pyhmmer-doc +%description help +# ππ‘β¦οΈπ¦ PyHMMER [](https://github.com/althonos/pyhmmer/stargazers) + +*[Cython](https://cython.org/) bindings and Python interface to [HMMER3](http://hmmer.org/).* + +[](https://github.com/althonos/pyhmmer/actions) +[](https://codecov.io/gh/althonos/pyhmmer/) +[](https://pypi.org/project/pyhmmer) +[](https://anaconda.org/bioconda/pyhmmer) +[](https://aur.archlinux.org/packages/python-pyhmmer) +[](https://pypi.org/project/pyhmmer/#files) +[](https://pypi.org/project/pyhmmer/#files) +[](https://pypi.org/project/pyhmmer/#files) +[](https://choosealicense.com/licenses/mit/) +[](https://github.com/althonos/pyhmmer/) +[](https://git.embl.de/larralde/pyhmmer/) +[](https://github.com/althonos/pyhmmer/issues) +[](https://pyhmmer.readthedocs.io) +[](https://github.com/althonos/pyhmmer/blob/master/CHANGELOG.md) +[](https://pepy.tech/project/pyhmmer) +[](https://doi.org/10.5281/zenodo.4270012) + + +## πΊοΈ Overview + +HMMER is a biological sequence analysis tool that uses profile hidden Markov +models to search for sequence homologs. HMMER3 is developed and maintained by +the [Eddy/Rivas Laboratory](http://eddylab.org/) at Harvard University. + +`pyhmmer` is a Python package, implemented using the [Cython](https://cython.org/) +language, that provides bindings to HMMER3. It directly interacts with the +HMMER internals, which has the following advantages over CLI wrappers +(like [`hmmer-py`](https://pypi.org/project/hmmer/)): + +- **single dependency**: If your software or your analysis pipeline is + distributed as a Python package, you can add `pyhmmer` as a dependency to + your project, and stop worrying about the HMMER binaries being properly + setup on the end-user machine. +- **no intermediate files**: Everything happens in memory, in Python objects + you have control on, making it easier to pass your inputs to HMMER without + needing to write them to a temporary file. Output retrieval is also done + in memory, via instances of the + [`pyhmmer.plan7.TopHits`](https://pyhmmer.readthedocs.io/en/stable/api/plan7.html#pyhmmer.plan7.TopHits) + class. +- **no input formatting**: The Easel object model is exposed in the + [`pyhmmer.easel`](https://pyhmmer.readthedocs.io/en/stable/api/easel.html) + module, and you have the possibility to build a + [`DigitalSequence`](https://pyhmmer.readthedocs.io/en/stable/api/easel.html#pyhmmer.easel.DigitalSequence) + object yourself to pass to the HMMER pipeline. This is useful if your sequences are already + loaded in memory, for instance because you obtained them from another + Python library (such as [Pyrodigal](https://github.com/althonos/pyrodigal) + or [Biopython](https://biopython.org/)). +- **no output formatting**: HMMER3 is notorious for its numerous output files + and its fixed-width tabular output, which is hard to parse (even + [`Bio.SearchIO.HmmerIO`](https://biopython.org/docs/dev/api/Bio.SearchIO.HmmerIO.html) + is struggling on some sequences). +- **efficient**: Using `pyhmmer` to launch `hmmsearch` on sequences + and HMMs in disk storage is typically as fast as directly using the + `hmmsearch` binary (see the [Benchmarks section](#%EF%B8%8F-benchmarks)). + [`pyhmmer.hmmer.hmmsearch`](https://pyhmmer.readthedocs.io/en/stable/api/hmmer.html#hmmsearch) + uses a different parallelisation strategy compared to + the `hmmsearch` binary from HMMER, which can help getting the most of + multiple CPUs when annotating smaller sequence databases. + +*This library is still a work-in-progress, and in an experimental stage, +but it should already pack enough features to run biological analyses or +workflows involving `hmmsearch`, `hmmscan`, `nhmmer`, `phmmer`, `hmmbuild` +and `hmmalign`.* + + +## π§ Installing + +`pyhmmer` can be installed from [PyPI](https://pypi.org/project/pyhmmer/), +which hosts some pre-built CPython wheels for x86-64 Linux, as well as the +code required to compile from source with Cython: +```console +$ pip install pyhmmer +``` + +Compilation for UNIX PowerPC is not tested in CI, but should work out of the +box. Other architectures (e.g. Arm) and OSes (e.g. Windows) are not +supported by HMMER. + +A [Bioconda](https://bioconda.github.io/) package is also available: +```console +$ conda install -c bioconda pyhmmer +``` + + +## π Documentation + +A complete [API reference](https://pyhmmer.readthedocs.io/en/stable/api/) can +be found in the [online documentation](https://pyhmmer.readthedocs.io/), or +directly from the command line using +[`pydoc`](https://docs.python.org/3/library/pydoc.html): +```console +$ pydoc pyhmmer.easel +$ pydoc pyhmmer.plan7 +``` + + +## π‘ Example + +Use `pyhmmer` to run `hmmsearch` to search for Type 2 PKS domains +([`t2pks.hmm`](https://raw.githubusercontent.com/althonos/pyhmmer/master/pyhmmer/tests/data/hmms/txt/t2pks.hmm)) +inside proteins extracted from the genome of *Anaerococcus provencensis* +([`938293.PRJEB85.HG003687.faa`](https://raw.githubusercontent.com/althonos/pyhmmer/master/pyhmmer/tests/data/seqs/938293.PRJEB85.HG003687.faa)). +This will produce an iterable over +[`TopHits`] that can be used for further sorting/querying in Python. +Processing happens in parallel using Python threads, and a [`TopHits`] +object is yielded for every [`HMM`] passed in the input iterable. + +[`HMM`]: https://pyhmmer.readthedocs.io/en/stable/api/plan7.html#pyhmmer.plan7.HMM +[`TopHits`]: https://pyhmmer.readthedocs.io/en/stable/api/plan7.html#pyhmmer.plan7.TopHits + +```python +import pyhmmer + +with pyhmmer.easel.SequenceFile("pyhmmer/tests/data/seqs/938293.PRJEB85.HG003687.faa", digital=True) as seq_file: + sequences = list(seq_file) + +with pyhmmer.plan7.HMMFile("pyhmmer/tests/data/hmms/txt/t2pks.hmm") as hmm_file: + for hits in pyhmmer.hmmsearch(hmm_file, sequences, cpus=4): + print(f"HMM {hits.query_name.decode()} found {len(hits)} hits in the target sequences") +``` + +Have a look at more in-depth examples such as [building a HMM from an alignment](https://pyhmmer.readthedocs.io/en/stable/examples/msa_to_hmm.html), +[analysing the active site of a hit](https://pyhmmer.readthedocs.io/en/stable/examples/active_site.html), +or [fetching marker genes from a genome](https://pyhmmer.readthedocs.io/en/stable/examples/fetchmgs.html) +in the [Examples](https://pyhmmer.readthedocs.io/en/stable/examples/index.html) +page of the [online documentation](https://pyhmmer.readthedocs.io/). + + +## π Feedback + +### β οΈ Issue Tracker + +Found a bug ? Have an enhancement request ? Head over to the [GitHub issue +tracker](https://github.com/althonos/pyhmmer/issues) if you need to report +or ask something. If you are filing in on a bug, please include as much +information as you can about the issue, and try to recreate the same bug +in a simple, easily reproducible situation. + +### ποΈ Contributing + +Contributions are more than welcome! See [`CONTRIBUTING.md`](https://github.com/althonos/pyhmmer/blob/master/CONTRIBUTING.md) for more details. + + +## β±οΈ Benchmarks + +Benchmarks were run on a [i7-10710U CPU](https://ark.intel.com/content/www/us/en/ark/products/196448/intel-core-i7-10710u-processor-12m-cache-up-to-4-70-ghz.html) running @1.10GHz with 6 physical / 12 +logical cores, using a FASTA file containing 4,489 protein sequences extracted +from the genome of *Escherichia coli* +([`562.PRJEB4685`](https://progenomes.embl.de/genome.cgi)) +and the version 33.1 of the [Pfam](https://pfam.xfam.org/) HMM library containing +18,259 domains. Commands were run 3 times on a warm SSD. *Plain lines show +the times for pressed HMMs, and dashed-lines the times for HMMs in text format.* + + + +Raw numbers can be found in the [`benches` folder](https://github.com/althonos/pyhmmer/blob/master/benches/). +They suggest that `phmmer` should be run with the number of *logical* cores, +while `hmmsearch` should be run with the number of *physical* cores (or less). +A possible explanation for this observation would be that HMMER +platform-specific code requires too many [SIMD](https://en.wikipedia.org/wiki/SIMD) +registers per thread to benefit from [simultaneous multi-threading](https://en.wikipedia.org/wiki/Simultaneous_multithreading). + +To read more about how PyHMMER achieves better parallelism than HMMER for +many-to-many searches, have a look at the [Performance page](https://pyhmmer.readthedocs.io/en/stable/performance.html) +of the documentation. + + +## π See Also + +Building a HMM from scratch? Then you may be interested in the [`pyfamsa`](https://pypi.org/project/pyfamsa/) +package, providing bindings to [FAMSA](https://github.com/refresh-bio/FAMSA), +a very fast multiple sequence aligner. In addition, you may want to trim alignments: +in that case, consider [`pytrimal`](https://pypi.org/project/pytrimal), which +wraps [trimAl 2.0](https://github.com/inab/trimal/tree/2.0_RC). + +If despite of all the advantages listed earlier, you would rather use HMMER +through its CLI, this package will not be of great help. You can instead check +the [`hmmer-py`](https://github.com/EBI-Metagenomics/hmmer-py) package developed +by [Danilo Horta](https://github.com/horta) at the [EMBL-EBI](https://www.ebi.ac.uk). + + +## βοΈ License + +This library is provided under the [MIT License](https://choosealicense.com/licenses/mit/). +The HMMER3 and Easel code is available under the +[BSD 3-clause](https://choosealicense.com/licenses/bsd-3-clause/) license. +See `vendor/hmmer/LICENSE` and `vendor/easel/LICENSE` for more information. + +*This project is in no way affiliated, sponsored, or otherwise endorsed by +the [original HMMER authors](http://hmmer.org/). It was developed by +[Martin Larralde](https://github.com/althonos/pyhmmer) during his PhD project +at the [European Molecular Biology Laboratory](https://www.embl.de/) in +the [Zeller team](https://github.com/zellerlab).* + + +%prep +%autosetup -n pyhmmer-0.7.3 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-pyhmmer -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Wed Apr 12 2023 Python_Bot <Python_Bot@openeuler.org> - 0.7.3-1 +- Package Spec generated @@ -0,0 +1 @@ +b623d0ac844844e58e798cc44c51949a pyhmmer-0.7.3.tar.gz |