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docs/abacus.md

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+Aggregate data from multiple experiments and adjusts label-free quantification to accurately account for peptides shared across multiple proteins
+
+
+## Usage
+
+`philosopher abacus [flags] [folders]`
+
+
+## flags
+
+`--comb`
+
+A pre formed combined protXML file. See below how to create one.
+
+`--labels`
+
+Indicates whether the data sets include TMT labels or not.
+
+`--pepProb`
+
+Minimum peptide probability (default 0.5).
+
+`--picked`
+
+Apply the picked FDR algorithm before the protein scoring.
+
+`--prtProb`
+
+Minimum protein probability (default 0.9).
+
+`--razor`
+
+Use razor peptides for protein FDR scoring.
+
+`--tag`
+
+Decoy tag (default "rev_").
+
+`--uniqueonly`
+
+Report TMT quantification based on only unique peptides.
+
+
+## Example
+
+Aggregating data from 3 different experiments, in 3 different workspaces
+
+`philosopher abacus control/ treatment_1/ treatment_2/`
+
+Aggregating data from 3 different experiments, in 3 different workspaces and using a pre existing protXML combined file.
+
+`philosopher abacus --comb combined.potxml control/ treatment_1/ treatment_2/`
+
+
+## FAQ
+
+_What exactly do I need to do before running Abacus ?_
+
+You need to work on each individual experiment workspace before running Abacus. Each folder containing individual experimental data must be converted to a Workspace and must have its data analyzed by the filter command.
+
+_I don't have a combined protXML file, how do I get one?_
+
+You need to execute ProteinProphet using all pepXML files from each individual folder you are analyzing.
+
+_Where should I execute the abacus command ?_
+
+The command should be execute one level above the experimental data
+
+_This seems to be a lot of work, isn't there any workaround ?_
+
+Yes, take a look at the [Pipeline](pipeline.md) command.

docs/analytics.md

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+### Analytics
+
+In order to maintain a statistics regarding the program usage, Philospher reports to on-line servers every time it is used
+for a new project.
+
+
+## Is the program collecting data from my computer?
+No! No data is collected from your user, computer, network or work environment. The program is not constantly collecting anything nor monitoring time-based, activity-based or behavioral-based usage.
+
+
+## What kind of data Philosopher is reporting back ?
+We take advantage of Google Analytics for usage report, it is the same technology used by thousands of websites to monitor users. Differently from all those web pages, we are __not__ monitoring user behavior, the only piece of information collected is the geographical location of the user and the current time.
+
+
+## Why you just don't use the download count as a usage statistics ?
+Download links are objects sitting in the wild on the Internet which is full of bots and web crawlers programmed to collect data and scrutinize websites like GitHub. This means that download counters will be an over estimation on the true number of users enjoying Philosopher.
+
+
+## Are you sure no other data is been collected ?
+Yes! If you have any concerns, feel free to check the source code.
+
+
+## Can I turn this option off ?
+Yes, you can. Reporting is absolutely optional and it will not reflect on or limit your experience with the program.
+When creating a new workspace, just add the parameter `--analytics false` to it.

docs/available-software.md

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+### Available Software
+
+Philosopher provides easy access to the following third-party software:
+
+* [ProteoWizard msconvert](https://www.nature.com/articles/nbt.2377)
+
+* [ProteoWizard idconvert](https://www.nature.com/articles/nbt.2377)
+
+* [Comet](http://onlinelibrary.wiley.com/doi/10.1002/pmic.201200439/abstract)
+
+* [PeptideProphet](http://peptideprophet.sourceforge.net/pep-proph.pdf)
+
+* [ProteinProphet](http://proteinprophet.sourceforge.net/prot-proph.pdf)
+
+* [iProphet](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3237071/)
+
+* [PTMProphet](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4506239/)
+
+
+### Available Implementations
+
+The following algorithms are available as complete or partial *native* implementations:
+
+* [moFF](http://www.nature.com/nmeth/journal/v13/n12/full/nmeth.4075.html)
+
+* [Abacus](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3113614/)

docs/cluster.md

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+Sequence-based protein reports using a clustering approach to assemble a high-level report.
+
+
+## Usage
+
+`philosopher cluster [flags]`
+
+
+## Flags
+
+`--id`
+
+UniProt proteome ID for retrieving annotation features.
+
+`--level`
+
+cluster identity level (default 0.9)
+
+
+## Example
+
+Clustering all reported proteins with at least 85% identity level.
+
+`philosopher cluster --level 0.85`
+
+Clustering all reported proteins and retrieving annotation data from UniProt.
+
+`philosopher cluster --id UP000005640`

docs/comet.md

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+Peptide Spectrum Matching using the Comet database search engine.
+
+
+## Version
+Comet release 2017.01 rev. 4
+
+
+## Usage
+
+`philosopher comet [flags] [files]`
+
+
+## Flags
+
+`--print`
+
+Print the default parameter file to the local directory.
+
+`--param`
+
+Points the location of the parameter file for the analysis.
+
+
+## Example
+
+Execute Comet using the parameter file _param.txt_, and using 2 converted raw files _sample1_ and _sample2_. Comet will analyze them one at a time using the specified parameters.
+
+`philosopher comet --param param.txt sample1.mzml sample2.mzml`

docs/constraints.md

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+### Are there any constraints ?
+
+* One of the major source of problems using custom pipelines like Philosopher originates from badly formatted FASTA databases. Philosopher works with NCBI and UniProt databases or a database with headers formatted using the NCBI or [UniProt specification](http://www.uniprot.org/help/fasta-headers). If your FASTA file contains headers with different formatting we strongly suggest you to format them following the guidelines from one of the suggested on line Databases mentioned above.
+
+* Philosopher currently only supports mzML files, if you have other format you will need to convert them to mzML (only important if you opt for doing quantification).

docs/database.md

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+The _Database_ command can be used to prepare a protein FASTA file for the following analysis. The database can be downloaded using the UniProt Proteome ID or by using a pre-formed FASTA file.
+
+
+## Usage
+
+`philosopher database [flags]`
+
+
+## Flags
+
+`--add`
+
+Allows you to add one or more custom sequences to your database. Only UniProt FASTA formatting is allowed.
+
+`--annotate`
+
+Process a ready-to-use database.
+
+`--contam`
+
+Add 116 common contaminants found in LC-MS/MS experiments. More information can be found [here](http://www.thegpm.org/crap/).
+
+`--custom`
+
+Skips the downloading of a fresh database and use an existing one instead. The custom file will also be used to create decoys and contaminants if desired.
+
+`--enzyme`
+
+The name of the enzyme for the digestion. The options are:
+
+* trypsin
+* lys_c
+* lys_n
+* chymotrypsin
+
+The default option is _trypsin_.
+
+`--id`
+
+The Proteome ID used to find and download an organism proteome. See below where to find the ID.
+
+`--isoform`
+
+Allows isoform sequences to be added to the download.
+
+`--prefix`
+
+Decoy prefix to be added, default is _rev__.
+
+`--reviewed`
+
+Download only reviewed sequences from Swiss-Prot.
+
+
+## Examples
+
+Download a complete human proteome snapshot without isoforms, using Trypsin for protein digestion and adding contaminants.
+
+`philosopher database --id UP000005640 --contam`
+
+Download the reviewed version of the human proteome, containing isoforms and contaminants.
+
+`philospher database --id UP000005640 --reviewed --contam`
+
+Prepare a custom protein FASTA file for the analysis (skip the download).
+
+`philosopher database --custom protein.fas --contam`
+
+Download the complete human proteome and add external sequences from another FASTA file.
+
+`philosopher database --id UP000005640 -add spikes.fas`
+
+This example will download all reference sequences from the Human proteome, contaminants will be added to the database with the rev_ prefix and the resulting file will be digested using Lys C.
+
+`philosopher database --contam --enzyme lys_c --reviewed --id UP000005640`
+
+
+## FAQ
+
+_Where can I find the UniProt Proteome ID for my organism?_
+
+The list of all existing UniProt Identifiers can be found [here](http://www.uniprot.org/proteomes/). Before using Philosopher, you need to search the UniProt website for the correct id.

docs/documentation.md

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+# Documentation
+
+Here you will find some more information about Philosopher's commands and functionalities.
+
+
+## About
+
+[Compatible Operating Systems](operating-systems.md)
+
+[Available Software](available-software.md)
+
+[The Prophets](prophets.md)
+
+[Constraints](constraints.md)
+
+
+## Commands
+
+
+### Workspace management
+
+[Workspace](workspace.md)
+
+
+### Database handling
+
+[Database](database.md)
+
+
+### Database search
+
+[Comet](comet.md)
+
+
+### Peptide and protein validation
+
+[PeptideProphet](peptideProphet.md)
+
+[iProphet](iProphet.md)
+
+[ProteinProphet](proteinProphet.md)
+
+[PTMProphet](ptmprophet.md)
+
+
+### Statistical scoring and FDR evaluation
+
+[Filter](filter.md)
+
+
+### Label-free quantification
+
+[Freequant](freequant.md)
+
+
+### Isotope quantification
+
+[Labelquant](labelquant.md)
+
+
+### Homology-based protein Report
+
+[Cluster](cluster.md)
+
+
+### Multi experiment combined analysis
+
+[Abacus](abacus.md)
+
+
+### Peptide and protein report
+[Report](report.md)
+
+
+### Automated analysis
+[Pipeline](pipeline.md)