# Protein Turnover
protein turnover computations
Install with:
```bash
pip install protein-turnover
# If you plan to use non-western text for your job names maybe also install unidecode
# pip install Unidecode
# *OR*
pip install protein-turnover[unidecode]
```
This will give you a `turnover` command (equivalent to `python -m protein_turnover`).
## The Turnover Job File
To run protein-turnover you need to create a jobfile (which is in [toml format](https://toml.io)).
e.g.:
```toml
# job name is a display name and should contain information about what the job is about.
job_name = "My Experiment"
pepxml = "chx_cc_repeat.interact.pep.xml"
protxml = "chx_cc_repeat.combined.prot.xml"
# a list of mzML files
mzmlfiles = [ "milla009642.mzML"]
# internal job identifier (*optional* used to create auxilary filenames)
jobid = "job1"
# for cached data. If not specifies cache files will be placed in the
# same directories as original datafiles
cache_dir = "."
# email is *optional*
email = "me.lastname@uwa.edu.au"
[settings]
# these are the default settings
rtTolerance = 15.0
mzTolerance = 1e-5
labelledIsotopeNumber = 15
labelledElement = "N"
maximumLabelEnrichment = 0.95
retentionTimeCorrection = "SimpleMedian"
useObservedMz = false
minProbabilityCutoff = 0.8
enrichmentColumns = 10
```
So a minimal jobfile would be (say):
```toml
job_name = "My Experiment"
pepxml = "chx_cc_repeat.interact.pep.xml"
protxml = "chx_cc_repeat.combined.prot.xml"
mzmlfiles = [ "milla009642.mzML"]
```
### Notes:
- `email` will only work if the `config.MAIL_SERVER` is correct.
- `job_name` is really just a human readable short description of the job.
- `jobid` is used (mainly) to create filenames; for example the final sqlite output file will
be called `{jobid}.sqlite`
- File names that are not absolute are relative to the _current working directory_ of the turnover process.
- If `[settings]` is missing the values will default to the example values above. You only
need to specify values that are different from the ones above.
- `cache_dir`: see below.
## Running a Job
```bash
turnover run {jobfile}.toml
# *OR*
python -m protein_turnover run {jobfile}.toml
# alter configuration and use info level logging and log to logfile.log
turnover --level=info --logfile=logfile.log run {jobfile}.toml
```
### Cache Files and `cache_dir`
Turnover translates all the `.mzML`, `pep.xml`, and `prot.xml` files into pandas DataFrames
stored in `.parquet` [format](https://parquet.apache.org/), plus an internal (to turnover) format that make it easy to quickly scan spectra using [`mmap`](https://docs.python.org/3/library/mmap.html).
These files are cached in `cache_dir` based on an sha256 hash of the contents of each file.
Thus re-runs of the job don't need to (re)-generate these files again.
Because of the sha256 hash you can used a single `cache_dir` for _all_ jobs.
If the cache files are deleted, they will be recreated when the job is run again.
If `cache_dir` is not specified the the
cached files will be placed in the same directory as the originator xml files.
## Viewing
One the job has run you can view the results in a browser
```bash
pip install protein-turnover-website
turnover view {jobfile}.toml
```
# Windows
A default install of python on [windows](https://www.python.org/downloads/windows/)
Will give you a `py` function instead of a `python` function. Go to the search bar and type `cmd`. In
the `cmd` shell you should use instead of `turnover ...` `py -m protein_turnver ...`
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"description": "# Protein Turnover\n\nprotein turnover computations\n\nInstall with:\n\n```bash\npip install protein-turnover\n# If you plan to use non-western text for your job names maybe also install unidecode\n# pip install Unidecode\n# *OR*\npip install protein-turnover[unidecode]\n```\n\nThis will give you a `turnover` command (equivalent to `python -m protein_turnover`).\n\n## The Turnover Job File\n\nTo run protein-turnover you need to create a jobfile (which is in [toml format](https://toml.io)).\n\ne.g.:\n\n```toml\n# job name is a display name and should contain information about what the job is about.\njob_name = \"My Experiment\"\npepxml = \"chx_cc_repeat.interact.pep.xml\"\nprotxml = \"chx_cc_repeat.combined.prot.xml\"\n# a list of mzML files\nmzmlfiles = [ \"milla009642.mzML\"]\n# internal job identifier (*optional* used to create auxilary filenames)\njobid = \"job1\"\n# for cached data. If not specifies cache files will be placed in the\n# same directories as original datafiles\ncache_dir = \".\"\n# email is *optional*\nemail = \"me.lastname@uwa.edu.au\"\n\n[settings]\n# these are the default settings\nrtTolerance = 15.0\nmzTolerance = 1e-5\nlabelledIsotopeNumber = 15\nlabelledElement = \"N\"\nmaximumLabelEnrichment = 0.95\nretentionTimeCorrection = \"SimpleMedian\"\nuseObservedMz = false\nminProbabilityCutoff = 0.8\nenrichmentColumns = 10\n```\n\nSo a minimal jobfile would be (say):\n\n```toml\njob_name = \"My Experiment\"\npepxml = \"chx_cc_repeat.interact.pep.xml\"\nprotxml = \"chx_cc_repeat.combined.prot.xml\"\nmzmlfiles = [ \"milla009642.mzML\"]\n```\n\n### Notes:\n\n- `email` will only work if the `config.MAIL_SERVER` is correct.\n- `job_name` is really just a human readable short description of the job.\n- `jobid` is used (mainly) to create filenames; for example the final sqlite output file will\n be called `{jobid}.sqlite`\n- File names that are not absolute are relative to the _current working directory_ of the turnover process.\n- If `[settings]` is missing the values will default to the example values above. You only\n need to specify values that are different from the ones above.\n- `cache_dir`: see below.\n\n## Running a Job\n\n```bash\nturnover run {jobfile}.toml\n# *OR*\npython -m protein_turnover run {jobfile}.toml\n\n# alter configuration and use info level logging and log to logfile.log\nturnover --level=info --logfile=logfile.log run {jobfile}.toml\n```\n\n### Cache Files and `cache_dir`\n\nTurnover translates all the `.mzML`, `pep.xml`, and `prot.xml` files into pandas DataFrames\nstored in `.parquet` [format](https://parquet.apache.org/), plus an internal (to turnover) format that make it easy to quickly scan spectra using [`mmap`](https://docs.python.org/3/library/mmap.html).\n\nThese files are cached in `cache_dir` based on an sha256 hash of the contents of each file.\nThus re-runs of the job don't need to (re)-generate these files again.\n\nBecause of the sha256 hash you can used a single `cache_dir` for _all_ jobs.\n\nIf the cache files are deleted, they will be recreated when the job is run again.\n\nIf `cache_dir` is not specified the the\ncached files will be placed in the same directory as the originator xml files.\n\n## Viewing\n\nOne the job has run you can view the results in a browser\n\n```bash\npip install protein-turnover-website\nturnover view {jobfile}.toml\n```\n\n# Windows\n\nA default install of python on [windows](https://www.python.org/downloads/windows/)\nWill give you a `py` function instead of a `python` function. Go to the search bar and type `cmd`. In\nthe `cmd` shell you should use instead of `turnover ...` `py -m protein_turnver ...`\n",
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