--- title: "synaptome.data database for synaptome.db" author: - name: Oksana Sorokina affiliation: The School of Informatics, University of Edinburgh, Edinburgh, UK email: oksana.sorokina@ed.ac.uk - name: Anatoly Sorokin affiliation: Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, UK email: a.sorokin@liverpool.ac.uk - name: J. Douglas Armstrong affiliation: The School of Informatics, University of Edinburgh, Edinburgh, UK output: BiocStyle::html_document: self_contained: yes toc: true toc_float: true toc_depth: 2 code_folding: show date: "`r doc_date()`" package: "`r pkg_ver('synaptome.data')`" vignette: > %\VignetteIndexEntry{data_vignette} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r setup, include = FALSE} knitr::opts_chunk$set( collapse = TRUE, comment = "#>", crop = NULL ## Related to https://stat.ethz.ch/pipermail/bioc-devel/2020-April/016656.html ) ``` ```{r vignetteSetup, echo=FALSE, message=FALSE, warning = FALSE} ## Track time spent on making the vignette startTime <- Sys.time() ## Bib setup library("RefManageR") ## Write bibliography information bib <- c( R = citation(), BiocStyle = citation("BiocStyle")[1], knitr = citation("knitr")[1], RefManageR = citation("RefManageR")[1], rmarkdown = citation("rmarkdown")[1], sessioninfo = citation("sessioninfo")[1], synaptome.data = citation("synaptome.data")[1] ) ``` # Basics Genes encoding synaptic proteins are highly associated with neuronal disorders, many of which show clinical co-morbidity. Authors of `r Citep(bib[["synaptome.data"]])` integrated 58 published synaptic proteomic datasets that describe over 8000 proteins. They combined protein datasets with direct protein-protein interactions and functional metadata to build a database. Analysis of that database reveals the shared and unique protein components that underpin multiple disorders. The `synaptome.data` provides Bioconductor with access to the public version of that database . ## Install `synaptome.data` `R` is an open-source statistical environment which can be easily modified to enhance its functionality via packages. `r Biocpkg("synaptome.data")` is a `R` package available via the [Bioconductor](http://bioconductor.org) repository for packages. `R` can be installed on any operating system from [CRAN](https://cran.r-project.org/) after which you can install `r Biocpkg("synaptome.data")` by using the following commands in your `R` session: ```{r "install", eval = FALSE} if (!requireNamespace("BiocManager", quietly = TRUE)) { install.packages("BiocManager") } BiocManager::install("synaptome.data") ## Check that you have a valid Bioconductor installation BiocManager::valid() ``` ## Required knowledge `r Biocpkg("synaptome.data")` is based on many other packages and in particular in those that have implemented the infrastructure needed for dealing with RNA-seq data (EDIT!). That is, packages like `r Biocpkg("SummarizedExperiment")` (EDIT!). If you are asking yourself the question "Where do I start using Bioconductor?" you might be interested in [this blog post](http://lcolladotor.github.io/2014/10/16/startbioc/#.VkOKbq6rRuU). ## Asking for help As package developers, we try to explain clearly how to use our packages and in which order to use the functions. But `R` and `Bioconductor` have a steep learning curve so it is critical to learn where to ask for help. The blog post quoted above mentions some but we would like to highlight the [Bioconductor support site](https://support.bioconductor.org/) as the main resource for getting help: remember to use the `synaptome.data` tag and check [the older posts](https://support.bioconductor.org/t/synaptome.data/). Other alternatives are available such as creating GitHub issues and tweeting. However, please note that if you want to receive help you should adhere to the [posting guidelines](http://www.bioconductor.org/help/support/posting-guide/). It is particularly critical that you provide a small reproducible example and your session information so package developers can track down the source of the error. ## Citing `synaptome.data` We hope that `r Biocpkg("synaptome.data")` will be useful for your research. Please use the following information to cite the package and the overall approach. Thank you! ```{r "citation"} ## Citation info citation("synaptome.data") ``` # Quick start to using to `synaptome.data` ```{r "start", message=FALSE, eval=FALSE} library("synaptome.data") ahub <- AnnotationHub::AnnotationHub(hub='http://127.0.0.1:9393/') sdb<-AnnotationHub::query(ahub,'SynaptomeDB') ``` Here is an example of you can cite your package inside the vignette: * `r Biocpkg("synaptome.data")` `r Citep(bib[["synaptome.data"]])` # Reproducibility The `r Biocpkg("synaptome.data")` package `r Citep(bib[["synaptome.data"]])` was made possible thanks to: * R `r Citep(bib[["R"]])` * `r Biocpkg("BiocStyle")` `r Citep(bib[["BiocStyle"]])` * `r CRANpkg("knitr")` `r Citep(bib[["knitr"]])` * `r CRANpkg("RefManageR")` `r Citep(bib[["RefManageR"]])` * `r CRANpkg("rmarkdown")` `r Citep(bib[["rmarkdown"]])` * `r CRANpkg("sessioninfo")` `r Citep(bib[["sessioninfo"]])` This package was developed using `r BiocStyle::Biocpkg("biocthis")`. Code for creating the vignette ```{r createVignette, eval=FALSE} ## Create the vignette library("rmarkdown") system.time(render("data_vignette.Rmd", "BiocStyle::html_document")) ## Extract the R code library("knitr") knit("data_vignette.Rmd", tangle = TRUE) ``` Date the vignette was generated. ```{r reproduce1, echo=FALSE} ## Date the vignette was generated Sys.time() ``` Wallclock time spent generating the vignette. ```{r reproduce2, echo=FALSE} ## Processing time in seconds totalTime <- diff(c(startTime, Sys.time())) round(totalTime, digits = 3) ``` `R` session information. ```{r reproduce3, echo=FALSE} ## Session info library("sessioninfo") options(width = 120) session_info() ``` # Bibliography This vignette was generated using `r Biocpkg("BiocStyle")` `r Citep(bib[["BiocStyle"]])` with `r CRANpkg("knitr")` `r Citep(bib[["knitr"]])` and `r CRANpkg("rmarkdown")` `r Citep(bib[["rmarkdown"]])` running behind the scenes. Citations made with `r CRANpkg("RefManageR")` `r Citep(bib[["RefManageR"]])`. ```{r vignetteBiblio, results = "asis", echo = FALSE, warning = FALSE, message = FALSE} ## Print bibliography PrintBibliography(bib, .opts = list(hyperlink = "to.doc", style = "html")) ```