This is a preliminary version of RiboFlow that can process libraries prepared with Unique Molecular Identifiers (UMIs).

RiboFlow extracts UMIs and stores them in the Fastq headers and uses the UMIs in deduplication ( instead of position based read collapsing ). For this purpose RiboFlow uses umi_tools.

Install umi_tools.

conda install -c bioconda -c conda-forge umi_tools

Note that umi_tools is not in the Docker image of RiboFlow yet (coming soon though). So DO NOT RUN Riboflow using the Docker Image for UMI runs.

See also project.yaml in this repo.

The following parameter must be set:

dedup_method: "umi_tools"

Also, depending on the organization of the UMI sequences, users must set the following two parameters:

umi_tools_extract_arguments: "-p \"^(?P<umi_1>.{12})(?P<discard_1>.{4}).+$\" --extract-method=regex"
umi_tools_dedup_arguments:   "--read-length"

The above example takes the first 12 nucleotides from the 5' end, discards the 4 nucleotides downstream and writes the 12 nt UMI sequence to the header. The second parameter tells umi_tools to use read lengths IN ADDITION to UMI sequencing in collapsing reads. Note that these two arguments are directly provided to umi_tools. So users are encouraged to familirize themselves with umi_tools.

RiboFlow.groovy file has been updated to incorporate umi_tools. So existing users need to replace their RiboFlow.groovy with the new one in this repository.

In the current version UMIs for only ribosome profiling libraries are supported. So RNA-Seq libraries can either be used without deduplication or the reads can be collapsed based on position.