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ENCODExplorer: A compilation of metadata from ENCODE
====================================================================
Audrey Lemacon, Louis Gendron, Charles Joly Beauparlant and Arnaud Droit.

This package and the underlying ENCODExplorer code are distributed under 
the Artistic license 2.0. You are free to use and redistribute this software. 

"The ENCODE (Encyclopedia of DNA Elements) Consortium is an international 
collaboration of research groups funded by the National Human Genome Research 
Institute (NHGRI). The goal of ENCODE is to build a comprehensive parts list of 
functional elements in the human genome, including elements that act at the 
protein and RNA levels, and regulatory elements that control cells and 
circumstances in which a gene is active"^[source : [ENCODE Projet Portal ](https://www.encodeproject.org/)] .

However, data retrieval and downloading can be really time-consuming using 
the current web portal. 

This package has been designed to facilitate data access by compiling the 
metadata associated with file, experiment and dataset. 

We first extract ENCODE schema from its public github repository. 
Then we identify the main entities and their relationship with each other to 
rebuild the ENCODE database into a data.table. 
We also developped a function which can extract the essential metadata in a R 
object to aid data exploration.
We implemented time-saving features to select ENCODE files by querying their 
metadata and download them.

The data.table can be regenerated at will to query ENCODE database locally 
keep it up-to-date.

This vignette will introduce the way to update ENCODE data.

### Loading ENCODExplorer package

```{r libraryLoad}
suppressMessages(library(ENCODExplorer))
```

### Data update

If you want regenerate ENCODExplorer data, you can use the update function.
When you use `overwrite = TRUE`, it will overwrite the default package data, 
otherwise it will return the datatable `encode_df` .

```{r, eval=FALSE}
# the path (relative or absolute) to the future database
database_filename <- "new.encode.rda"
new_data <- export_ENCODEdb_matrix(database_filename, overwrite = FALSE)
```

If you want to update the data manually or partially, you have to process the 
following steps:

* generate a list of data tables from ENCODE: 

```{r tables, eval=FALSE}
# the path (relative or absolute) to the future database
database_filename = "new.encode.rda"
tables = prepare_ENCODEdb(database_filename)
```

* generate the metadata encode_df from a list of data.table:
```{r new_encode_df, eval = FALSE}
new_encode_df <- export_ENCODEdb_matrix(tables)
```


The whole process will take several minutes (30 to 60 minutes depending on your
work environment)

### Updated data usage

If you have chosen not to overwrite the default data, you can use your newly 
created data.
Once the `new_encode_df` is generated, you can use it to replace the default one 
in the `queryEncode` and `downloadEncode` function by setting the *df* option of those 
functions.

```{r queryEncode, eval=FALSE}
query_results <- queryEncode(df = new_encode_df, assay = "switchgear", target ="elavl1", file_format = "bed" , fixed = F)
downloadEncode(df = new_encode_df, file_acc = query_results$file_accession)
```

Be sure to use the same referencial *df* for both **queryEncode** and **downloadEncode**.

You can also use the list of data.table database for own purpose. The imputed database 
model is available in the [dedicated vignette](DBmodel.html)
