LTRpred: de novo annotation of intact retrotransposons (RStudio Server Version)
1.9K
The LTRpred pipeline allows users to de novo annotate functional and thus potentially mobile retrotransposons in any given genome assembly. Different from other annotation tools, LTRpred focuses on retrieving structurally intact elements within sequences of genomes rather than characterizing all traces of historic TE activity.
Such functional annotation is most useful when trying to spot retrotransposons responsible for the recent reshuffling of genetic material in the tree of life. Detecting and further characterisation of those active retrotransposons yield the potential to harness them as mutagenesis agents by inducing transposition bursts in a controlled fashion to stimulate genomic reshaping processes towards novel traits.
Users can consult a detailed LTRpred documentation to learn more about all available features.
drostlab/ltrpred_rstudio container for use with RStudio Server# retrieve docker image from dockerhub
docker pull drostlab/ltrpred_rstudio
# run ltrpred container
docker run -e PASSWORD=ltrpred --rm -p 8787:8787 -ti drostlab/ltrpred_rstudio
To open RStudio and interact with the container go to your standard web browser and type in the following url:
http://localhost:8787
Username: rstudio
Password: ltrpred
Users can choose a custom password if they wish.
Within RStudio you can now run the example:
LTRpred::LTRpred(genome.file = system.file("Hsapiens_ChrY.fa", package = "LTRpred"))
Users can exit the container by pressing Ctrl + c multiple times.
Now, users can add their own genome data as well as the Dfam database for
further annotation to the drostlab/ltrpred_rstudio container by following these steps (in a different Terminal window):
# go to the folder path in which you want to
# store all genome and Dfam data you want to
# mount in the ltrpred container and then run:
# create a new folder which will store
# all files that will be required in the
# ltrpred container
mkdir ltrpred_data
cd ltrpred_data
# create a dfam database folder
mkdir Dfam
cd Dfam
Now users can download and format the Dfam database as follows (within the Dfam folder created above). Unfortunately, the Dfam database size is too large to make it part of the drostlab/ltrpred_rstudio container. In addition, the database is frequently curated and updated. Thus, it is recommended that users download and format the Dfam database to their local hard drive and mount it to the running drostlab/ltrpred_rstudio container.
To format the Dfam database locally, users need to install HMMER on their local machine (to use hmmpress). However, within the drostlab/ltrpred and drostlab/ltrpred_rstudio containers HMMER is already preinstalled and does not need to be installed by the user. An example installation of HMMER for Linux machines is listed below.
For macOS users, please install wget on your masOS machine using Homebrew.
wget https://www.dfam.org/releases/Dfam_3.1/families/Dfam.hmm.gz
gunzip Dfam.hmm.gz
# format database by running hmmpress
hmmpress Dfam.hmm
cd ..
Next, make sure to also store the genome assembly file (in fasta format) you
want to de novo annotate with LTRpred in the ltrpred_data folder you just created.
A possible way to retrieve such a genome is (within R) using biomartr.
If you use biomartr please make sure to install all biomartr package dependencies before running the following code.
# install.packages("biomartr")
biomartr::getGenome(db = "ensembl",
organism = "Saccharomyces cerevisiae",
path = "yeast_genome",
gunzip = TRUE)
The respective genome assembly file is now stored at yeast_genome/Saccharomyces_cerevisiae.R64-1-1.dna.toplevel.fa and needs to be copied
into the ltrpred_data folder you just created.
Next, users can mount their ltrpred_data folder to the RStudio server run
the same way they mounted folders in the command line container version (using -v).
This folder mounting can also be run within the RStudio Terminal of the drostlab/ltrpred_rstudio container.
# retrieve docker image from dockerhub
docker pull drostlab/ltrpred_rstudio
# run ltrpred container
docker run -e PASSWORD=ltrpred --rm -p 8787:8787 -v /put/here/your/path/to/ltrpred_data:/home/rstudio/ltrpred_data -ti drostlab/ltrpred_rstudio
Now go to your standard web browser and type in the following url:
http://localhost:8787
Username: rstudio
Password: ltrpred
In RStudio type:
list.files()
You should be able to see the ltrpred_data folder.
Users can exit the container by pressing Ctrl + c multiple times.
Content type
Image
Digest
Size
1.6 GB
Last updated
over 6 years ago
docker pull drostlab/ltrpred_rstudio