recipe scramble

Soft Clipped Read Alignment Mapper







doi: 10.1038/s41436-020-0749-x

SCRAMble identifies clusters of soft clipped reads in a BAM file, builds consensus sequences, aligns to representative L1Ta, AluYa5, and SVA-E sequences, and outputs MEI calls

package scramble

(downloads) docker_scramble



depends bioconductor-rsamtools:


depends htslib:


depends libgcc-ng:


depends r-base:


depends r-optparse:


depends r-rblast:


depends r-stringr:




You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install scramble

and update with::

   mamba update scramble

To create a new environment, run:

mamba create --name myenvname scramble

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `scramble/tags`_ for valid values for ``<tag>``)


SCRAMble runs as a two-step process. First cluster_identifier is used to generate soft-clipped read cluster consensus sequences. Second, SCRAMble.R analyzes the cluster file for likely MEIs. Custom wrapper script is provided to help setting location of SCRAMble.R script, and values for --install-dir and --mei-refs params.

Download stats