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cpanse authored Jul 27, 2022
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![](https://github.com/fgcz/bfabric/workflows/R-CMD-check-bfabric/badge.svg)

# bfabric R package
# bfabricShiny R package

enables connecting R and bfabric using REST
## Demonstration

1. enables connecting R and bfabric using REST

![bfabricPy-read-R](https://user-images.githubusercontent.com/4901987/65041207-7c757c80-d956-11e9-90ca-9c3e2e0ca724.gif)

2. command line triggered analytics

# INSTALL
![code_snippet_demo](https://user-images.githubusercontent.com/4901987/181242377-a9bf3988-b193-494c-91c9-a010500ee3f2.gif)

```{r}
## R --no-save < code_snippet.R
## devtools::install_github("fgcz/bfabricShiny")
## devtools::install_github("fgcz/rawDiag")
stopifnot(R.Version()['major'] >= '4',
require('rawDiag'),
require('bfabricShiny'))
## Define B-Fabric input workunit
workunitid <- 165473
## Query metadata from B-Fabric
Q <- bfabricShiny::read(login, webservicepassword,
endpoint = 'resource',
query = list('workunitid' = workunitid), as_data_frame=FALSE)
## setting root directory
rawfilenames <- Q$res |>
sapply(function(x)file.path('/srv/www/htdocs/', x$relativepath))
## Extract MS data from BLOBs using the rawDiag R package
## That requires storage access via SSH, NFS, or SAMBA
RAW <- rawfilenames |>
parallel::mclapply(rawDiag::read.raw, mc.cores = 12) |>
base::Reduce(f = rbind)
## Print a summary
RAW |> rawDiag::summary.rawDiag()
## Have fun with visualization https://doi.org/10.1021/acs.jproteome.8b00173
## (a)
RAW |> rawDiag::PlotPrecursorHeatmap(bins = 25)
## (b)
RAW |> rawDiag::PlotPrecursorHeatmap(bins = 25) +
ggplot2::facet_wrap(~ filename)
## (c)
RAW |> rawDiag::PlotTicBasepeak(method = 'overlay')
## (d)
RAW |> rawDiag::PlotInjectionTime(method = 'overlay')
```


## INSTALL

```{bash}
apt-get install r-base libcurl4-openssl-dev
Expand All @@ -28,8 +74,7 @@ devtools::install_github('fgcz/bfabricShiny', build_vignettes = FALSE, quiet = F
```


# Demonstration

# Use cases

## Run shiny based queue generator application

Expand Down Expand Up @@ -284,49 +329,3 @@ The idea is to fetch a RData file stored in bfabric.



## Command Line Triggered Visual Exploration


![code_snippet_demo](https://user-images.githubusercontent.com/4901987/181242377-a9bf3988-b193-494c-91c9-a010500ee3f2.gif)


```{r}
## R --no-save < code_snippet.R
## devtools::install_github("fgcz/bfabricShiny")
## devtools::install_github("fgcz/rawDiag")
stopifnot(R.Version()['major'] >= '4',
require('rawDiag'),
require('bfabricShiny'))
## Define B-Fabric input workunit
workunitid <- 165473
## Query metadata from B-Fabric
Q <- bfabricShiny::read(login, webservicepassword,
endpoint = 'resource',
query = list('workunitid' = workunitid), as_data_frame=FALSE)
## setting root directory
rawfilenames <- Q$res |>
sapply(function(x)file.path('/srv/www/htdocs/', x$relativepath))
## Extract MS data from BLOBs using the rawDiag R package
## That requires storage access via SSH, NFS, or SAMBA
RAW <- rawfilenames |>
parallel::mclapply(rawDiag::read.raw, mc.cores = 12) |>
base::Reduce(f = rbind)
## Print a summary
RAW |> rawDiag::summary.rawDiag()
## Have fun with visualization https://doi.org/10.1021/acs.jproteome.8b00173
## (a)
RAW |> rawDiag::PlotPrecursorHeatmap(bins = 25)
## (b)
RAW |> rawDiag::PlotPrecursorHeatmap(bins = 25) +
ggplot2::facet_wrap(~ filename)
## (c)
RAW |> rawDiag::PlotTicBasepeak(method = 'overlay')
## (d)
RAW |> rawDiag::PlotInjectionTime(method = 'overlay')
```

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