Shiny Rmarkdown

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  1. Shiny Rmarkdown Pokemon
  2. Shiny Presentation

R: shiny+Rmarkdown. Bootstraplib: Tools for styling shiny and rmarkdown from R via Bootstrap (3 or 4) Sass. R Markdown: The Definitive Guide (conversion) Yihui Xie, Joseph J. Allaire, Garrett Grolemund download Z-Library. Download books for free.

DOI: 10.18129/B9.bioc.crossmeta

Cross Platform Meta-Analysis of Microarray Data

Bioconductor version: Release (3.12)

  1. The traditional way to add Shiny components to an R Markdown document is through the use of runtime: shiny. This method provides a very straightforward development experience (you can use Shiny UI and server functions anywhere you like within the document).
  2. 오픈 소스 R 프로그래밍 언어를 사용하여 대규모 데이터 세트에서 통계 계산 및 그래픽 작업 수행.
  3. Data Scientist Jared Lander demonstrates how you can integrate Shiny into RMarkdown with ease.This lesson is an excerpt from the video course Shiny R LiveLes.

Implements cross-platform and cross-species meta-analyses of Affymentrix, Illumina, and Agilent microarray data. This package automates common tasks such as downloading, normalizing, and annotating raw GEO data. The user then selects control and treatment samples in order to perform differential expression analyses for all comparisons. After analysing each contrast seperately, the user can select tissue sources for each contrast and specify any tissue sources that should be grouped for the subsequent meta-analyses.

Author: Alex Pickering

Maintainer: Alex Pickering <alexvpickering at>

Citation (from within R, enter citation('crossmeta')):


To install this package, start R (version '4.0') and enter:

For older versions of R, please refer to the appropriate Bioconductor release.



To view documentation for the version of this package installed in your system, start R and enter:

HTMLR Scriptcrossmeta vignette
PDFReference Manual


biocViewsAnnotation, BatchEffect, DifferentialExpression, GUI, GeneExpression, Microarray, OneChannel, Preprocessing, Software, TissueMicroarray, Transcription
In Bioconductor sinceBioC 3.4 (R-3.3) (4.5 years)
LicenseMIT + file LICENSE
DependsR (>= 4.0)
Importsaffy(>= 1.52.0), affxparser(>= 1.46.0), AnnotationDbi(>= 1.36.2), Biobase(>= 2.34.0), BiocGenerics(>= 0.20.0), BiocManager (>= 1.30.4), DT (>= 0.2), DBI (>= 1.0.0), data.table (>= 1.10.4), fdrtool (>= 1.2.15), GEOquery(>= 2.40.0), limma(>= 3.30.13), matrixStats (>= 0.51.0), metaMA (>= 3.1.2), miniUI (>= 0.1.1), oligo(>= 1.38.0), reader (>= 1.0.6), RColorBrewer (>= 1.1.2), RCurl (>=, RSQLite (>= 2.1.1), randomcoloR (>=, stringr (>= 1.2.0), sva(>= 3.22.0), shiny (>= 1.0.0), shinyjs (>= 2.0.0), shinyBS (>= 0.61), shinyWidgets (>= 0.5.3), shinypanel (>= 0.1.0), statmod (>= 1.4.34), XML (>=, readxl (>= 1.3.1)
Suggestsknitr, rmarkdown, lydata,, testthat
SystemRequirementslibxml2: libxml2-dev (deb), libxml2-devel (rpm) libcurl: libcurl4-openssl-dev (deb), libcurl-devel (rpm) openssl: libssl-dev (deb), openssl-devel (rpm), libssl_dev (csw), [email protected] (brew)
Depends On Me
Imports Me
Suggests Meccmap
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Shiny Rmarkdown Pokemon

Source Package crossmeta_1.16.1.tar.gz
Windows Binary (32- & 64-bit)
macOS 10.13 (High Sierra) crossmeta_1.16.1.tgz
Source Repositorygit clone
Source Repository (Developer Access)git clone [email protected]:packages/crossmeta
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Package Downloads ReportDownload Stats
Old Source Packages for BioC 3.12Source Archive

5.3 Shiny

By adding Shiny to a dashboard, you can let viewers change underlying parameters and see the results immediately, or let dashboards update themselves incrementally as their underlying data changes (see functions reactiveFileReader() and reactivePoll() in the shiny package). This is done by adding runtime: shiny to a standard dashboard document, and then adding one or more input controls and/or reactive expressions that dynamically drive the appearance of the components within the dashboard.

Using Shiny with flexdashboard turns a static R Markdown report into an interactive document. It is important to note that interactive documents need to be deployed to a Shiny Server to be shared broadly (whereas static R Markdown documents are standalone web pages that can be attached to emails or served from any standard web server).

Note that the shinydashboard package provides another way to create dashboards with Shiny.

5.3.1 Getting started

Shiny Presentation

The steps required to add Shiny components to a dashboard are:

  1. Add runtime: shiny to the options declared at the top of the document (YAML metadata).

  2. Add the {.sidebar} attribute to the first column of the dashboard to make it a host for Shiny input controls (note that this step is not strictly required, but this will generate a typical layout for Shiny-based dashboards).

  3. Add Shiny inputs and outputs as appropriate.

  4. When including plots, be sure to wrap them in a call to renderPlot(). This is important not only for dynamically responding to changes, but also to ensure that they are automatically re-sized when their container changes.

5.3.2 A Shiny dashboard example

Here is a simple example of a dashboard that uses Shiny (see Figure 5.7 for the output):

FIGURE 5.7: An interactive dashboard based on Shiny.

The first column includes the {.sidebar} attribute and two Shiny input controls; the second column includes the Shiny code required to render the chart based on the inputs.

One important thing to note about this example is the chunk labeled global at the top of the document. The global chunk has special behavior within flexdashboard: it is executed only once within the global environment, so that its results (e.g., data frames read from disk) can be accessed by all users of a multi-user dashboard. Loading your data within a global chunk will result in substantially better startup performance for your users, and hence is highly recommended.

5.3.3 Input sidebar

You add an input sidebar to a flexdashboard by adding the {.sidebar} attribute to a column, which indicates that it should be laid out flush to the left with a default width of 250 pixels and a special background color. Sidebars always appear on the left no matter where they are defined within the flow of the document.

If you are creating a dashboard with multiple pages, you may want to use a single sidebar that applies across all pages. In this case, you should define the sidebar using a first-level Markdown header.

5.3.4 Learning more

Below are some good resources for learning more about Shiny and creating interactive documents:

  1. The official Shiny website ( includes extensive articles, tutorials, and examples to help you learn more about Shiny.

  2. The article “Introduction to Interactive Documents” on the Shiny website is a great guide for getting started with Shiny and R Markdown.

  3. For deploying interactive documents, you may consider Shiny Server or RStudio Connect: