In KasperThystrup/EncircleR: EncircleR
library(EncircleR)
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
EncircleR
The goal of EncircleR is to automate and streamline circRNA analysis, by providing a graphical interface for selecting and downloading reference files, Perform read trimming and read mapping, and finally to perform circRNA detection by exploring backsplice junction contents.
Installation
Third party software
In order to use the tools provided in this guide, and to install the required dependencies, the following external software must be installed:
Dependencies
- libgit2: [Ubuntu 20.04 LTS], [Arch Linux], [Mac Homebrew]
- gcc-fortran: [Ubuntu 20.04 LTS], [Arch Linux], [Mac installation instructions]
- R: [Ubuntu], [Arch linux], [Mac]
- RStudio: [Ubuntu & Mac], [Arch linux]
Tools
EncircleR envokes different bioinformatic tools in order to process raw reads and quantify genes and circRNAs. These tools must be installed and the path to their binary execution file must be noted.
The following tools are evoked during the pipeline:
In this guide, I utilize Miniconda to install these tools, as it easily handles the depedenencies of these tools. Also, the path to the local binary execution files are easy to locate.
Miniconda depends on Python3 so in order to make sure it is installed, the following command should determine its installation path. If you yield an error message, it is not installed.
```{bash, eval=FALSE}
which python3
Install Python3, if it is not installed. [[Ubuntu 20.04](https://packages.ubuntu.com/focal/python3)], [[Arch Linux](https://wiki.archlinux.org/index.php/python)], [[Mac](https://www.python.org/downloads/mac-osx/)]
Next, download and install Miniconda, following their own guide. [Download](https://docs.conda.io/en/latest/miniconda.html) and [Installation instructions](https://conda.io/projects/conda/en/latest/user-guide/install/index.html).
Note the installation folder (Defaults to: `/home/[YOUR USER]/miniconda3`), it is relevant for the next step. Also, if chosing `[yes]` to initialise conda on terminal startup, make sure to restart the terminal to ensure that it is initialized.
#### Installing Tools with Miniconda
Install the fastp and STAR-aligner by executing the following command.
```{bash, eval=FALSE}
conda install -c bioconda fastp
conda install -c bioconda star
Finally, we need to note the path to the binary execution file, when installed through Miniconda, these can be located from the Miniconda installation folder.
The tools should be located at:
/home/[YOUR USER]/miniconda3/bin/STAR/home/[YOUR USER]/miniconda3/bin/fastp
Now we are set up for installing the R packages.
R package dependencies
EncircleR uses the circulaR R package for performing circRNA detection. Therefore, in order to install EncircleR, the circulaR pacakge along with its dependencies, must be installed.
The following Biocodncutor packages are dependencies of both the circulaR and the EncircleR package:
circulaR:
- AnnotationDbi
- BiocGenerics
- BSgenome
- DESeq2
- ensembldb
- GenomeInfoDb
- GenomicFeatures
- GenomicRanges
- Gviz
- IRanges
- Rsamtools
- S4Vectors
EncircleR:
- AnnotationHub
- S4Vectors
- plyranges
install.packages("BiocManager")
BiocManager::install(c("AnnotationDbi", "BiocGenerics", "BSgenome", "DESeq2", "ensembldb", "GenomeInfoDb", "GenomicFeatures", "GenomicRanges", "Gviz", "IRanges", "Rsamtools", "S4Vectors", "AnnotationHub", "S4Vectors", "plyranges"))
Install from GitHub with devtools
The devtools R package must be installed, to enable easy installation of circulaR and EncircleR from github.
install.packages("devtools", dependencies = TRUE)
devtools::install_github("https://github.com/KasperThystrup/circulaR")
devtools::install_github("https://github.com/KasperThystrup/EncircleR")
How to use
Setup
In this example four Paired end Total RNA samples are downloaded from the ENA browser. These can be found and downloaded from ENA Browser:
After downloading, a metadata sheet containing sample information must be set up.
The pipeline takes the following format:
- A sample name column
- A file path column
- A Read mate column
- A Name column
knitr::kable(x = EncircleR::meta_example, caption = "An example metadata sheet")
Execution
Start the graphical interface with the following command.
EncircleR::run_app()
Generation of experiment folder
This starts the browser which greets you with the Experimental Setup panel.
First, select and upload the metadata file, Next fill out the full path to an output experiment folder (in this example it is ~/Demonstration), and press Setup Experiment. This sets up an experimental folder system, where sample data are either copied (safest) or moved (fastest). It also generates an updated metadata table within the experiment folder (~/Demonstration/metadata.tsv), which contains the filepaths to the samples within the experiment folder, and which should be used for future reruns.
Selection of reference data
The first time you run this app, you have to download and set up a reference genome. EncircleR utilizes Ensembl for reference genome and gene models. Currently, the latest version supported are release 100. On subsequent runs, chose the correct version from the Chose an existing reference genome drop-down menu.
Click New Reference Genome to set up a new reference genome, and select an organism from the Organism drop-down menu, this causes the app to query Ensembl for available Ensembl releases. Use the slider to select a release version. Once ready, press Download Reference files to download the genome and gene models. Note that progress is not shown, so expect some waiting.
Once finished, fill out the STAR Index menu by providing the full path to the STAR-aligner binary execution file (e.g. ~/miniconda3/bin/STAR), define the amount of cores as well as read length, and press Prepare STAR index to initaite the STAR aligner to generate a complete index of the reference genome. This step takes a long time, which is especially affected by the amount of selected cores.
Once finished head to the Choose an existing reference genome drop-down menu, and head on to the Read preparation tab. !NOTE! if the latest reference genome does not show up in the selection box, restart the app and use the new metadata.tsv file in the experiment directory (e.g. ~/Demonstration/metadata.tsv), as it contains the updated locations and file names of the samples. This should update the list with the latest genome index.
Head to the Read preparation tab.
Read preparation
Now that a reference genome index have been generated, sample read data are ready for processing. The first step is to remove low quality reads as well as to ensure trimming of low quality base calls. Provide an amount of available cores and click Begin read QC and Trimming.
Once finished, a STAR aligner menu shows up. Again, select amount of desired cores and click Begin alignment. This step will take some time.
Once the progress bar disapears, head on to the CircRNA analysis tab.
CircRNA analysis
Enter an experiment name which is used in a file name to save the circRNA data, at the end of the circRNA detection. To enable reloading the data, mind that the filename is case sensitive and can contain no special characters.
Once ready, select amount of cores and press Perform circRNA analysis. This inititates the circulaR circRNa detection algorithm. This step will likewise take a while.
Once finished, a Filtration menu shows up. This menu enables you to filter out backsplice junctions which may be noisy. Use the top slider to set a minimal threshold for how many samples each backsplice junction must occur in. Use the buttomn slider to determine the minimal threshold for the minimal read counts, each unique backsplice junction must have to be considered a circRNA.
Once satisfied, press Filter reads. To save the results press Save object.
Results
Results are now generated and Mapping statistics as well as backsplice junction statistics can be reviewed in the Statistics tab.
Head on to the Detected circRNA tab and press Generate circRNA table to make a table of detected circRNAs.
KasperThystrup/EncircleR documentation built on March 21, 2021, 10:13 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
library(EncircleR) knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
EncircleR
The goal of EncircleR is to automate and streamline circRNA analysis, by providing a graphical interface for selecting and downloading reference files, Perform read trimming and read mapping, and finally to perform circRNA detection by exploring backsplice junction contents.
Installation
Third party software
In order to use the tools provided in this guide, and to install the required dependencies, the following external software must be installed:
Dependencies
- libgit2: [Ubuntu 20.04 LTS], [Arch Linux], [Mac Homebrew]
- gcc-fortran: [Ubuntu 20.04 LTS], [Arch Linux], [Mac installation instructions]
- R: [Ubuntu], [Arch linux], [Mac]
- RStudio: [Ubuntu & Mac], [Arch linux]
Tools
EncircleR envokes different bioinformatic tools in order to process raw reads and quantify genes and circRNAs. These tools must be installed and the path to their binary execution file must be noted.
The following tools are evoked during the pipeline:
In this guide, I utilize Miniconda to install these tools, as it easily handles the depedenencies of these tools. Also, the path to the local binary execution files are easy to locate.
Miniconda depends on Python3 so in order to make sure it is installed, the following command should determine its installation path. If you yield an error message, it is not installed. ```{bash, eval=FALSE} which python3
Install Python3, if it is not installed. [[Ubuntu 20.04](https://packages.ubuntu.com/focal/python3)], [[Arch Linux](https://wiki.archlinux.org/index.php/python)], [[Mac](https://www.python.org/downloads/mac-osx/)] Next, download and install Miniconda, following their own guide. [Download](https://docs.conda.io/en/latest/miniconda.html) and [Installation instructions](https://conda.io/projects/conda/en/latest/user-guide/install/index.html). Note the installation folder (Defaults to: `/home/[YOUR USER]/miniconda3`), it is relevant for the next step. Also, if chosing `[yes]` to initialise conda on terminal startup, make sure to restart the terminal to ensure that it is initialized. #### Installing Tools with Miniconda Install the fastp and STAR-aligner by executing the following command. ```{bash, eval=FALSE} conda install -c bioconda fastp conda install -c bioconda star
Finally, we need to note the path to the binary execution file, when installed through Miniconda, these can be located from the Miniconda installation folder.
The tools should be located at:
/home/[YOUR USER]/miniconda3/bin/STAR/home/[YOUR USER]/miniconda3/bin/fastp
Now we are set up for installing the R packages.
R package dependencies
EncircleR uses the circulaR R package for performing circRNA detection. Therefore, in order to install EncircleR, the circulaR pacakge along with its dependencies, must be installed.
The following Biocodncutor packages are dependencies of both the circulaR and the EncircleR package:
circulaR:
- AnnotationDbi
- BiocGenerics
- BSgenome
- DESeq2
- ensembldb
- GenomeInfoDb
- GenomicFeatures
- GenomicRanges
- Gviz
- IRanges
- Rsamtools
- S4Vectors
EncircleR:
- AnnotationHub
- S4Vectors
- plyranges
install.packages("BiocManager") BiocManager::install(c("AnnotationDbi", "BiocGenerics", "BSgenome", "DESeq2", "ensembldb", "GenomeInfoDb", "GenomicFeatures", "GenomicRanges", "Gviz", "IRanges", "Rsamtools", "S4Vectors", "AnnotationHub", "S4Vectors", "plyranges"))
Install from GitHub with devtools
The devtools R package must be installed, to enable easy installation of circulaR and EncircleR from github.
install.packages("devtools", dependencies = TRUE) devtools::install_github("https://github.com/KasperThystrup/circulaR") devtools::install_github("https://github.com/KasperThystrup/EncircleR")
How to use
Setup
In this example four Paired end Total RNA samples are downloaded from the ENA browser. These can be found and downloaded from ENA Browser:
After downloading, a metadata sheet containing sample information must be set up. The pipeline takes the following format:
- A sample name column
- A file path column
- A Read mate column
- A Name column
knitr::kable(x = EncircleR::meta_example, caption = "An example metadata sheet")
Execution
Start the graphical interface with the following command.
EncircleR::run_app()
Generation of experiment folder
This starts the browser which greets you with the Experimental Setup panel.
First, select and upload the metadata file, Next fill out the full path to an output experiment folder (in this example it is ~/Demonstration), and press Setup Experiment. This sets up an experimental folder system, where sample data are either copied (safest) or moved (fastest). It also generates an updated metadata table within the experiment folder (~/Demonstration/metadata.tsv), which contains the filepaths to the samples within the experiment folder, and which should be used for future reruns.
Selection of reference data
The first time you run this app, you have to download and set up a reference genome. EncircleR utilizes Ensembl for reference genome and gene models. Currently, the latest version supported are release 100. On subsequent runs, chose the correct version from the Chose an existing reference genome drop-down menu.
Click New Reference Genome to set up a new reference genome, and select an organism from the Organism drop-down menu, this causes the app to query Ensembl for available Ensembl releases. Use the slider to select a release version. Once ready, press Download Reference files to download the genome and gene models. Note that progress is not shown, so expect some waiting.
Once finished, fill out the STAR Index menu by providing the full path to the STAR-aligner binary execution file (e.g. ~/miniconda3/bin/STAR), define the amount of cores as well as read length, and press Prepare STAR index to initaite the STAR aligner to generate a complete index of the reference genome. This step takes a long time, which is especially affected by the amount of selected cores.
Once finished head to the Choose an existing reference genome drop-down menu, and head on to the Read preparation tab. !NOTE! if the latest reference genome does not show up in the selection box, restart the app and use the new metadata.tsv file in the experiment directory (e.g. ~/Demonstration/metadata.tsv), as it contains the updated locations and file names of the samples. This should update the list with the latest genome index.
Head to the Read preparation tab.
Read preparation
Now that a reference genome index have been generated, sample read data are ready for processing. The first step is to remove low quality reads as well as to ensure trimming of low quality base calls. Provide an amount of available cores and click Begin read QC and Trimming.
Once finished, a STAR aligner menu shows up. Again, select amount of desired cores and click Begin alignment. This step will take some time.
Once the progress bar disapears, head on to the CircRNA analysis tab.
CircRNA analysis
Enter an experiment name which is used in a file name to save the circRNA data, at the end of the circRNA detection. To enable reloading the data, mind that the filename is case sensitive and can contain no special characters.
Once ready, select amount of cores and press Perform circRNA analysis. This inititates the circulaR circRNa detection algorithm. This step will likewise take a while.
Once finished, a Filtration menu shows up. This menu enables you to filter out backsplice junctions which may be noisy. Use the top slider to set a minimal threshold for how many samples each backsplice junction must occur in. Use the buttomn slider to determine the minimal threshold for the minimal read counts, each unique backsplice junction must have to be considered a circRNA.
Once satisfied, press Filter reads. To save the results press Save object.
Results
Results are now generated and Mapping statistics as well as backsplice junction statistics can be reviewed in the Statistics tab.
Head on to the Detected circRNA tab and press Generate circRNA table to make a table of detected circRNAs.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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