diff --git a/README.md b/README.md
index da63c80..a0e8049 100644
--- a/README.md
+++ b/README.md
@@ -140,479 +140,15 @@ are available at [Zenodo (manuscript_data)](https://sandbox.zenodo.org/record/12
- _time_course_analysis_ runs differential analysis for time-course experiments in pairwise fashion for consecutive time points
- _metabologram_integration_ pathway-based integration between *labeled targeted metabolomic* and *trascriptomic* data, resulting in metabologram plots
-All the analyses must be in a structure that is explained in the section [Organising your data for the analysis](#organising-your-data-for-the-analysis).
-Once the structure is ready, the generic command for running each analysis is:
+All the analyses must be in a specific folder structure. Once the structure is ready, the **generic command** for running each analysis is:
```commandline
python -m dimet -cd config -cn GENERAL_CONFIGURATION_FILENAME
```
+## Documentation
------------------------------------------------------------------------------------------------------
-# Organising your data for the analysis
-
-## Input data folder structure
-
-DIMet relies on a specific folder organisation for input data and the accompanying configuration files.
-Data should be structured following the example `MYPROJECT` below.
-
-```
-MYPROJECT
-├── config
-│ ├── analysis
-│ │ ├── dataset
-│ │ │ └── # --->'dataset configuration' yml files
-│ │ ├── # --->'analysis configuration' yml files
-│ ├── # ---> 'general configuration' yml files
-└── data
- └── DATANAME1_data
- └── raw
- ├── # ---> raw .csv files
-
-```
-
-`DATANAME1` represents an experiment, you should replace it by a meaningful name.
-More than one subfolder in the `data` folder can be present.
-
-### Data files
-
-The user has to provide his data files within the data folder. Original data files themselves
-have to be placed in the `raw` subfolder along with a metadata file that contains the experimental setup corresponding to the data.
-
-Both quantification and metadata files must be provided as in .csv 'tab' delimited format.
-
-_Note_: if you provide at least one type of measure, you can still run some of the analyses, by making sure that the data you provide is suitable for the analysis that you choose.
-
-#### a. Metadata file
-The structure of the **metadata file** has to contain 6 columns named
-name_to_plot, timepoint,
-timenum, condition,
-compartment, original_name.
-
-
-
- Explanation of the metadata format
- (click to show/hide)
-
-
-Here is the semantics of the columns:
-
-- name_to_plot is the string that will appear on the figures produced by DIMet
-- condition is the experimental condition
-- timepoint is the sampling time as it is defined in your experimental setup
-(it is an arbitary string that can contain non numerical characters)
-- timenum is the numerical encoding of the timepoint
-- compartment is the name of the cellular compartment for which the measuring
-has been done (e.g. "endo", "endocellular", "cyto", etc)
-- original_name contains the column names that are provided in the quantification files
-
-_Example_:
-
-| name_to_plot | condition | timepoint | timenum | compartment | original_name |
-|--------------|-----------|-----------|---------|-------------|---------------|
-| Cond1 T0 | cond1 | T0 | 0 | comp_name | T0_cond_1 |
-| Cond1 T24 | cond1 | T24 | 24 | comp_name | T24_cond_1 |
-| Cond2 T0 | cond2 | T0 | 0 | comp_name | T0_cond_2 |
-| Cond3 T24 | cond2 | T24 | 24 | comp_name | T24_cond_2 |
-
-
-
-#### b. Quantification files
-
-Each quantification file is expected to correspond to one type of measure. Supported measure types are:
-
-1. Isotopologue absolute values
-2. Total metabolite abundances
-3. Mean enrichment (also called Fractional contribution)
-4. Isotopologue proportions
-
-
- Expected format of the quantification files with examples
- (click to show/hide)
-
-
-Each row in the quantification files contains measurements for a given metabolite. Expected columns are the following:
-- ID contains the molecule identifiers
-- All the other columns contain measures in numeric format (no letters or symbols, only numbers).
-
-_Note 1_: quantification columns' names have to match with the column original_name in the **metadata** file.
-_Note 2_: For the isotopologues, the ID must follow the convention: `metaboliteID_m+X` (for example: `AMP_m+4`, `cit_m+0`, `cit_m+1`)
-
-The total metabolites' Abundances file:
-
-| ID | T0_cond_1 | T24_cond_1 | T0_cond_2 | T24_cond_2 |
-|----------|------------|-------------|------------|------------|
-| PEP | 3364610.46 | 10250098.25 | 1124772.29 | 1035932.25 |
-| citrate | 5783654.51 | 5934305.65 | 3546334.99 | 3460334.88 |
-| fumarate | 354387.74 | 360087.74 | 334287.74 | 350387.74 |
-| OA | 9435186.33 | 9435186.33 | 9435186.33 | 9435186.33 |
-
-
-The Mean enrichment (also called Fractional contribution) file:
-
-
-| ID | T0_cond_1 | T24_cond_1 | T0_cond_2 | T24_cond_2 |
-|----------|-----------|------------|-----------|------------|
-| PEP | 0.5603 | 0.6391 | 0.9591 | 0.9553 |
-| citrate | 0.8057 | 0.8870 | 0.7809 | 0.6918 |
-| fumarate | 0.001 | 0 | 0.1508 | 0.1511 |
-| OA | 0.7030 | 0.7006 | 0.001 | 0 |
-
-
-The Isotopologue absolute values file:
-
-| ID | T0_cond_1 | T24_cond_1 | T0_cond_2 | T24_cond_2 |
-|---------|------------|------------|-----------|------------|
-| PEP_m+0 | 357354.66 | 387054.66 | 0 | 0 |
-| PEP_m+1 | 965435.68 | 975030.68 | 668.91 | 568.87 |
-| PEP_m+2 | 1435050.95 | 7987654.66 | 136749.05 | 137709.05 |
-| PEP_m+3 | 606769.17 | 900358.25 | 987354.33 | 897654.33 |
-
-
-The Isotopologue proportions file :
-
-
-| ID | T0_cond_1 | T24_cond_1 | T0_cond_2 | T24_cond_2 |
-|---------|-----------|------------|-----------|------------|
-| PEP_m+0 | 0.106 | 0.038 | 0.000 | 0.000 |
-| PEP_m+1 | 0.287 | 0.095 | 0.001 | 0.001 |
-| PEP_m+2 | 0.427 | 0.779 | 0.122 | 0.133 |
-| PEP_m+3 | 0.180 | 0.088 | 0.878 | 0.867 |
-
-
-
-
-
-#### c. Data files for the omics integration (optional)
-
-DIMet offers the possitibilty of pathway-based integration of the metabolome and the transcriptome though **metabolograms**.
-
-
- Data files required for omics integration (click to show/hide)
-
- Two data types are required:
-
- 1. Metabolite quantification files in the raw directory.
- 2. Results, provided by the user, of the differential analysis of the transcriptome data placed in the folder integration_files
-
- integration_files folder contains files with differentially expressed genes provided by the user as well as the pathways files.
-
- Thus the expected project data structure becomes:
-
- ```
- MYPROJECT
- ├── config
- │ ├── analysis
- │ │ ├── dataset
- │ │ │ └── # --->'dataset configuration' yml files
- │ │ ├── # --->'analysis configuration' yml files
- │ ├── # ---> 'general configuration' yml files
- └── data
- └── DATANAME1_data
- ├── integration_files # ---> NEW FOLDER
- │ ├── # ---> .csv files required for omics integration
- └── raw
- ├── # ---> raw .csv files
-
- ```
-
- * Files for differentially expressed genes (DEGs)
-
-Files for differentially expressed genes (DEGs) must be provided in the tab delimited .csv format. For each file:
-1. The rows represent the genes (except the first one, which is the header having the names of the columns)
-2. The columns provide the information to be integrated, two columns are compulsory:
- 1. the gene names, given as strings
- 2. the Fold-Changes (or the log2 Fold-Changes) in numeric format (no letters or symbols, only numbers)
-
-Formatting example of differentially expressed genes files:
-
-| log2FoldChange | gene_symbol |
-|-------------------|--------------|
-| -16.1660338229612 | GPI |
-| 3.32192809488736 | HK1 |
-| 2.32192809488736 | RPIA |
-| 0.807354922057604 | PFKL |
-
-
- * The *metabolites per pathway* and *genes or transcripts per pathway* files
-
- These files contain the user-provided metabolites and genes for each pathway. It is allowed for a metabolite or gene to appear in several pathways.
- Identifiers must match with those appearing in the quantification files in the raw folder. Gene names must match with those appearing in the DEGs file
-
-_Example_ for metabolites per pathway:
-
-| GLYCOLYSIS | PENTOSE_PHOSPHATE | ... |
-|------------|-------------------|-----|
-| Glucose_6P | Ribose_5P | ... |
-| Pyruvate | Xylulose_5P | ... |
-| PEP | Glucose_6P | ... |
-| ... | ... | ... |
-
-
-_Example_ for genes per pathway:
-
-| GLYCOLYSIS | PENTOSE_PHOSPHATE | ... |
-|------------|-------------------|-----|
-| GPI | RPIA | ... |
-| HK1 | PGD | ... |
-| PKFL | RBKS | ... |
-| ... | ... | ... |
-
-All these files must be provided in the tab delimited .csv format.
-
-
-
-
-### Configuration files
-
-As it is shown in the folder structure above, there are three types of configuration files,
-all of them in `.yaml` format:
-
-1. `dataset configuration` files: provide the quantifications and metadata file names that are themselves present in the `data` directory.
-
-2. `analysis configuration` files: indicates which analysis (e.g. "differential analysis") is to be run for which data file and with which parameters.
-
-3. `general configuration` files: configures the analysis to be run by both pointing to the `analysis configuration` and providing general information such as e.g. output folder names etc.
-
-
-
-
- How to organize the configuration files (click to show/hide)
-
- The user must place the configuration files in the `config` folder, as follows:
-* the *dataset configuration* files, inside the `config/analysis/dataset/` subfolder
-* the *analysis configuration* files, inside the `config/analysis/` subfolder
-* the *general configuration* files, directly inside the `config` folder
-*
- Example of a structure of the config folder
- (click to show/hide)
-
-
- ```
- config
- ├── analysis
- │ ├── dataset
- │ │ ├── dataname1_data.yaml
- │ │ └── dataname1_data_integrate.yaml # <-- if suitable
- │ ├── differential_analysis_pairwise_dataname1.yaml
- │ ├── enrichment_lineplot_dataname1.yaml
- │ ├── isotopologues_plot_dataname1.yaml
- │ ├── metabologram_abundance_dataname1.yaml
- │ ├── pca_plot_dataname1.yaml
- │ └── timecourse_analysis_dataname1.yaml
- ├── general_config_abundance_plot_dataname1.yaml
- ├── general_config_differential_analysis_dataname1.yaml
- ├── general_config_enrichment_lineplot_dataname1.yaml
- ├── general_config_isotopologues_plot_dataname1.yaml
- ├── general_config_metabologram_abundance_dataname1.yaml
- ├── general_config_pca_plot_dataname1.yaml
- └── general_config_timecourse_analysis_dataname1.yaml
-
- ```
-
-
-
-
-The next sections explain each type of these files. Furthermore, when analyzing your own data, you can
-use these configuration examples as templates and fill them coherently.
-
-The `# <-` comment inside the examples indicates the parts that the user must fill.
-
-
- The dataset configuration
-
- For each given dataset, there must exist a corresponding *dataset configuration* file, which is located inside the `config/analysis/dataset/` folder.
- This file must specify:
- - the name of the metadata file
- - the names of the quantification files
- - the "order" of the conditions, where the *control* is the first to be listed
-(note that the name assigned to the control condition can be different than the one
-we used in our data).
-
- - Note that the parameter `_target_` must **not** be changed.
- - If you do not have all the four types of quantification that are shown below, just delete
- the entire line making reference to the type of quantification that is absent.
-
- ```
- _target_: dimet.data.DatasetConfig
-
- label: # <- name of your dataset, fill after the colon
- name: # <- short description of your dataset, fill after the colon
- subfolder: DATANAME1_data # <- subfolder name in the data folder, change after the colon
-
- # ALWAYS WITHIN THE RAW SUBFOLDER
- metadata: # <- file name, fill after the colon
- abundances: # <- file name, fill after the colon
- mean_enrichment: # <- file name, fill after the colon
- isotopologue_proportions: # <- file name, fill after the colon
- isotopologues: # <- file name, fill after the colon
-
- conditions :
- - cond1 # <- first must be control, fill
- - cond2 # <- the rest of the conditions vertically listed
- ```
- This dataset configuration will be used by all the types of analysis we offer except the omics integration, see the section *The integration dataset configuration* for that purpose.
-
-
-
-
- Special case of dataset configuration: the integration dataset configuration (for omics integration)
-
- When performing the **omics integration** ,
- there must also exist a *dataset configuration* file specific for the integration,
- that will point to `integration_files` and `raw` subfolders.
-
- Note that the parameter `_target_` must **not** be changed.
-
- ```
- _target_: dimet.data.DataIntegrationConfig
-
- label: integrate_DATANAME1 # <- change after the colon
- name: # <- short description of your dataset
- subfolder: DATANAME1_data # <- subfolder name in the data folder, change after the colon
-
- conditions :
- - cond1 # <- first must be control
- - cond2 # <- the rest of the conditions vertically listed
-
- # ALWAYS WITHIN THE RAW SUBFOLDER
- metadata: # <- file name, fill after the colon
- abundances: # <- file name, fill after the colon
- mean_enrichment: # <- file name, fill after the colon
-
- # WITHIN THE INTEGRATION_FILES SUBFOLDER
- transcripts:
- - myDEG_1 # <- file name
-
- pathways:
- metabolites: # <- file name, change fill the colon
- transcripts: # <- file name, change fill the colon
-
- ```
-
-
-
-
-
-
-
-
-
- The analysis configuration
-
- The *analysis configuration* is located inside the `config/analysis/` folder.
- For each analysis to be performed, one analysis configuration file must exist.
- It indicates which is the type of analysis we want to run,
- on which dataset this analysis will be applied, and the parameters that are
- specific to that analysis.
-
-
- ```
- label: differential-analysis-DATANAME1 # <- change after the colon
-
- defaults:
- - dataset: # <- name of the dataset cofiguration file
- - method: differential_analysis # <- see 'Available analyses'
-
- comparisons :
- - [[cond2, T24], [cond1, T24]] # <-
-
- statistical_test:
- abundances: # <- see statistic test options, fill after the colon
- mean_enrichment: prm-scipy # <- see options, fill after the colon
- isotopologues: disfit # <- see options, fill after the colon
- isotopologue_proportions: ranksum # <- see options, fill after the colon
-
- ```
-
- Currently, the **statistic test options** are:
-
- `MW` (Mann-Whitney test), `KW` (Kruskall-Wallis test),
- `ranksum` (Wilcoxon's rank sum test), `Wcox` (Wilcoxon's signed rank test),
- `BrMu` (Brunner-Munzel test) , `prm-scipy` (permutation testing),
- `Tt` (t-test) and
- `disfit` (Fitting of the distribution of the z-scores).
-
- Note that the parameters in the *analysis configuration* must be coherent with our dataset.
-
-
-
- The analysis configuration for the omics integration
-
- The integration performed by DIMet displays the 'differential omics' in the form of Metabologram(s).
- The analysis configuration file:
-
- ```
- label: metabologram-using-abundance-DATANAME1 # <- change after the colon
-
- defaults:
- - dataset: # <- integration dataset config
- - method: metabologram_integration
-
- comparisons :
- - [[cond2, T24], [cond1, T24]] # <- see note (**)
-
- # running for total abundances
- statistical_test:
- abundances: # <- can be abundances OR mean_enrichment
-
- columns_metabolites:
- ID : metabolite
- values : # <- log2FC or FC, fill after the colon
-
- columns_transcripts:
- ID: # <- the gene symbols column name, fill after the colon
- values: # <- the numeric column name, fill after the colon
-
- compartment:
- en
- ```
- (`**`) each metabolomics comparison must match with a DEG file.
-
- If you need to run the integration using the differential mean enrichment,
- a separate analysis configuration file must be created.
-
-
-
-
-
-
-
- The general configuration
-
- The *general configuration* file is located directly inside the `config` folder. It must declare the name of its corrresponding *analysis configuration* file. Place yourself in `defaults:` then `- analysis:`, see below:
-
- ```
- hydra:
- job:
- chdir: true
- run:
- dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}/${analysis.dataset.label}-${analysis.method.label}
-
- defaults:
- - analysis: # <-- the 'analysis configuration' name, fill after the colon
-
- figure_path: figures
- table_path: tables
- ```
-
-
- This *general configuration* file also provides the parameters for generating the output folder names; keep these
- output parameters unmodified, so DIMet will generate the full output folders and files names
- automatically.
-
-
-
- Note that across all the types of configuration files, any referenced file name must be written without the extension.
-
-
-
-
-
- Examples of configuration files, with their respective datasets are provided
-in [Zenodo (manuscript_data)](https://sandbox.zenodo.org/record/1234735).
-Also complementary minimal datasets with their configuration files are provided in
-[Zenodo (minimal_examples)](https://sandbox.zenodo.org/record/1234736).
+The documentation of DIMet is found in its [Wiki](https://github.com/cbib/DIMet/wiki) page, which contains all the information that the user needs to build her/his own folder structure of data and configuration files, and to successfully run DIMet. The section **organising your data for the analysis** and its respective subsections in the [Wiki](https://github.com/cbib/DIMet/wiki) provide explanations and examples to the user.
-----------------------------------------------