Transposable element annotations used by Telescope.
Telescope is a computational method that provides accurate estimation of transposable element expression. It directly addresses uncertainty in fragment assignment by reassigning ambiguously mapped fragments to the most probable source transcript as determined within a Bayesian statistical model.
Running the pipeline on Biowulf
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Create a folder fastq and add all compressed RNA-seq fastq files to be run with extensions
_R1.fastq.gzand_R2.fastq.gz. Hardlinks and symlinks will also work. -
The wrapper script
run_ervTelescope.shcan be used to a. initialize output folder, b. dryrun and c. submit run to cluster
% ./run_ervTelescope.sh
Pipeline Dir: /gpfs/gsfs10/users/CCBR_Pipeliner/Pipelines/ervTelescope
Git Commit/Tag: 65f31ef9dad234266f456f37bc984886a7f56216
run_ervTelescope.sh
--> run ervTelescope pipeline
USAGE:
bash ./run_ervTelescope.sh -m/--runmode=<RUNMODE> -w/--workdir=<WORKDIR>
Required Arguments:
1. RUNMODE: [Type: String] Valid options:
*) init : initialize workdir
*) run : run with slurm
*) reset : DELETE workdir dir and re-init it
*) dryrun : dry run snakemake to generate DAG
*) unlock : unlock workdir if locked by snakemake
*) runlocal : run without submitting to sbatch
2. WORKDIR: [Type: String]: Absolute or relative path to the output folder with write permissions.a. initialize output folder
Output folder needs to be initialized with the following command:
% bash ./run_ervTelescope.sh -m/--runmode=init -w/--workdir=<PathToOutdir>b. dryrun
Next, we cd to the output folder and edit the config.yaml to provide the run-specific user defined data like location of input fastqs, location of bowtie2 reference, genome annotations in GTF format etc. Then, we can dryrun the pipeline to verify that we are ready to submit the run to the cluster with the following command:
% bash ./run_ervTelescope.sh -m/--runmode=dryrun -w/--workdir=<PathToOutdir>c. submit to cluster
The pipeline can be submitted to cluster using the following command:
% bash ./run_ervTelescope.sh -m/--runmode=run -w/--workdir=<PathToOutdir>The above command will submit the master job to the cluster which will the spawn individual snakemake rule-jobs. It returns the master jobid which can be used to track the progress pipeline using a command similar to :
% squeue -u $USER -j <JOBID>