app.Rmd

---
output: html_document
runtime: shiny_prerendered
author: Environmental Cheminformatics Group, LCSB, University of Luxembourg
title: "`r paste('Shinyscreen', packageVersion('shinyscreen'))`"
---

```{r, context='setup', include='false'}
library(data.table)
library(shinyscreen)
def_state <- new_state()
def_datafiles <- shinyscreen:::dtable(File=character(0),
                                      tag=character(0))
def_datatab <- shinyscreen:::dtable("tag"=factor(),
                                    "adduct"=factor(levels=shinyscreen:::DISP_ADDUCTS),
                                    "set"=factor())

def_summ_subset <- shinyscreen:::dtable("QA Column"=shinyscreen:::QA_FLAGS,
                                        "Select"=factor("il irrilevante",levels=c("il irrilevante",
                                                                                  "il buono",
                                                                                  "il cattivo")))
## RMassBank masks shiny::validate. Unmask it.
validate <- shiny::validate
## def_state$input$tab$tags <- def_datatab
rv_state <- list2rev(def_state)
compl_sets <- eventReactive(rv_state$input$tab$setid,
                            rv_state$input$tab$setid[,unique(set)])
## Reactive values to support some of the UI elements.
## rv_ui <- reactiveValues(datatab=def_tags)

## Update with data-files.
rv_dfiles <- reactiveVal(def_datafiles)

## Data-file table when loading.
rv_datatab <- reactiveVal(def_datatab)



```


# Configuration {.tabset}

## Inputs


<details>
<summary>Specify the project directory</summary>
This is where the output files and the state of the analysis will be
saved.
</details>
```{r, echo=FALSE}
actionButton(inputId = "project_b",
             label= "Project")

```

Current project directory is `r textOutput("project", inline=T)`

<details><summary>Load the compound list(s)</summary>
A compound list is composed of entries describing compounds. This
description is used to search for its spectrum in the data file. The
list is a table in the ***CSV*** format and contains these columns,

* ***ID*** : required column, must be filled; this is a user-defined
  ID, uniquely associated with a compound
  
* ***Name*** : this column can be left blank; if not, it should contain the
  names of the compounds
  
* ***SMILES*** : a _SMILES_ string, describing the structure of the
  compound; this entry can be left empty only if one of either
  ***Formula***, or ***mz*** entries are not
  
* ***Formula*** : a chemical formula of a compound; this field can be
  empty only if one of either ***SMILES***, or ***mz*** entries are
  not
  
* ***mz*** : mass of the ionised compound; this field can be left
  empty only if one of either ***SMILES***, or ***Formula*** is not
  
* ***CAS*** : the CAS number of the compound; it can be left empty

* ***RT*** : retention time of the MS1 peak in minutes, if known; can
  be left empty.
  
Only ***ID*** and one of ***SMILES***, ***Formula*** or ***mz*** must
be filled. When structure, or a formula of a compound is known, it is
also possible to look for various adducts in the sample. Of course,
scanning for completely unknown compounds is also supported by the
***mz*** column. In this case, ***mz*** is the mass of the ion.

It is strongly recommended to quote SMILES, names and formulas in the
CSV file used with Shinyscreen.
</details>
```{r, echo=FALSE}
actionButton(inputId = "comp_list_b",
             label= "Compound list(s)")

```

`r htmlOutput("comp_lists")`

<details><summary>Load compound set list (_setid_ table)</summary>
The compound lists can contain more entries than is necessary. Using
the _setid_ lists, it is possible to create _compound sets_ which
contain only those compounds that will actually be searched for in the
data files. A _setid table_ is a _CSV_ containing at least two
columns,

* ***ID*** : the ID entry from the compound list

* ***set*** : an user-defined set name.
</details>
```{r, echo=FALSE}
actionButton(inputId = "setid_b",
             label= "Load the setid table")

```

`r htmlOutput("setids", inline=T)`

## Data files
<details><summary>Load data files</summary>
Shinyscreen currently supports only the **mzML** file format. After
loading the files, set file tags in the file table (column
**tag**). Additionally, specify a set of compounds that is supposed
to be extracted from the file using the **set** column. Finally,
specify the **adduct** in the adduct column. In case of compounds
with unknown structure and formula, the adduct is ignored for obvious
reasons.
</details>
```{r, echo=FALSE}
actionButton(inputId = "datafiles_b",
             label= "Load data files.")

```




<details><summary>Assign tags to data files.</summary>
Each tag designates an unique file. Use the table below to assign
tags.
</details>

```{r, echo=FALSE}
rhandsontable::rHandsontableOutput("datafiles")

```




<details><summary>Assign sets to tags.</summary>
For each tag, assign a set and an adduct (if the structure information
exists, otherwise _adduct_ column is ignored).
</details>

```{r, echo=F}
rhandsontable::rHandsontableOutput("datatab")
```

## Extraction

### Spectra extraction based settings

<details><summary>MS1 coarse error</summary>

Extract all entries matching the target mass within this error in the
precursor table.
</details>
```{r, echo=F}
shinyscreen::mz_input(input_mz = "ms1_coarse",
                       input_unit = "ms1_coarse_unit",
                       def_mz = def_state$conf$tolerance[["ms1 coarse"]],
                       def_unit = "Da")
```

<details><summary>MS1 fine error</summary>

The precursor table masses can be of lower accuracy. Once there is a
match within the coarse error, it can be further checked versus the
fine error bounds directly in the mass spectrum.

</details>
```{r, echo=F}
shinyscreen::mz_input(input_mz = "ms1_fine",
                      input_unit = "ms1_fine_unit",
                      def_mz = def_state$conf$tolerance[["ms1 fine"]],
                      def_unit = "ppm")
```

<details><summary>MS1 EIC window</summary>

The mz interval over which the intensities are aggregated to generate
a chromatogram.

</details>
```{r, echo=F}