drostlab/ltrpred repository overview

⁠LTRpred: de novo annotation of intact retrotransposons

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.

⁠Using the drostlab/ltrpred container

⁠Download drostlab/ltrpred container for use with R command line

# retrieve docker image from dockerhub
docker pull drostlab/ltrpred
# run ltrpred container
docker run --rm -ti drostlab/ltrpred
# start R prompt within ltrpred container
~:/app# R

Within the ltrpred container R prompt run the ltrpred example:

LTRpred::LTRpred(genome.file = system.file("Hsapiens_ChrY.fa", package = "LTRpred"))

To exit R in the container run:

q()

And to exit the ltrpred container run:

~:/app# exit

Now, users can add their own genome data as well as the Dfam database for further annotation to the ltrpred 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 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 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.

Now users can mount the ltrpred_data folder to the ltrpred Docker container (using the -v option). This -v mounting option is also available for the RStudio container version and can also be run within the RStudio Terminal.

docker run --rm -p 8787:8787 -v /put/here/your/path/to/ltrpred_data:/app/ltrpred_data -ti ltrpred

Within the ltrpred Docker container the ltrpred_data folder is now stored in the working directory /app.

When running the ltrpred Docker container you should be able to see the mounted ltrpred_data folder as following:

~:/app# ls

latticeExtra_0.6-28.tar.gz
ltrpred_data
software_downloads

Next, users can again run the R prompt within the ltrpred Docker container to run LTRpred with the local data that was mounted:

~:/app# R

# run LTRpred on the yeast genome that was mounted
# to the ltrpred container from your local 'ltrpred_data' folder
LTRpred(genome.file = "ltrpred_data/yeast_genome/Saccharomyces_cerevisiae.R64-1-1.dna.toplevel.fa", cores = 2)

As you can see, within the ltrpred container R prompt the current working directory is /app.

To also include the Dfam database for further annotation users can specify the path to the Dfam folder:

# run LTRpred on the yeast genome that was mounted
# to the ltrpred container from your local 'ltrpred_data' folder
LTRpred(genome.file = "ltrpred_data/yeast_genome/Saccharomyces_cerevisiae.R64-1-1.dna.toplevel.fa", 
    annotate = "Dfam",
		Dfam.db = "ltrpred_data/Dfam", 
		cores = 2)

Please be aware that using the Dfam database for further annotation significantly increases the computation time of the LTRpred pipeline.