Package: ymp
YMP is a tool that makes it easy to process large amounts of NGS read
data. It comes “batteries included” with everything needed to
preprocess your reads (QC, trimming, contaminant removal), assemble
metagenomes, annotate assemblies, or assemble and quantify RNA-Seq
transcripts, offering a choice of tools for each of those procecssing
stages. When your needs exceed what the stock YMP processing stages
provide, you can easily add your own, using YMP to drive novel tools,
tools specific to your area of research, or tools you wrote yourself.Note:Intrigued, but think YMP doesn’t exactly fit your needs?Missing processing stages for your favorite tool? Found a bug?Open an issue, create a PR, or better yet, join the team!TheYMP documentationis available at
readthedocs.Features:batteries includedYMP comes with a large number ofStagesimplementing common read
processing steps. These stages cover the most common topics,
including quality control, filtering and sorting of reads, assembly
of metagenomes and transcripts, read mapping, community profiling,
visualisation and pathway analysis.For a complete list, check thedocumentationor thesource.get started quicklySimply point YMP at a folder containing read files, at a mapping
file, a list of URLs or even an SRA RunTable and YMP will configure
itself. Use tab expansion to complete your desired series of stages
to be applied to your data. YMP will then proceed to do your
bidding, downloading raw read files and reference databases as
needed, installing requisite software environments and scheduling
the execution of tools either locally or on your cluster.explore alternative workflowsNot sure which assembler works best for your data, or what the
effect of more stringent quality trimming would be? YMP is made for
this! By keeping the output of each stage in a folder named to match
the stack of applied stages, YMP can manage many variant workflows
in parallel, while minimizing the amount of duplicate computation
and storage.go beyond the beaten pathBuilt on top ofBiocondaandSnakemake, YMP is easily extended with
your own Snakefiles, allowing you to integrate any type of
processing you desire into YMP, including your own, custom made
tools. Within the YMP framework, you can also make use of the
extensions to the Snakemake language provided by YMP (default
values, inheritance, recursive wildcard expansion, etc.), making
writing rules less error prone and repetative.BackgroundBioinformatical data processing workflows can easily get very complex,
even convoluted. On the way from the raw read data to publishable
results, a sizeable collection of tools needs to be applied,
intermediate outputs verified, reference databases selected, and
summary data produced. A host of data files must be managed, processed
individually or aggregated by host or spatial transect along the way.
And, of course, to arrive at a workflow that is just right for a
particular study, many alternative workflow variants need to be
evaluated. Which tools perform best? Which parameters are right?  Does
re-ordering steps make a difference? Should the data be assembled
individually, grouped, or should a grand co-assembly be computed?
Which reference database is most appropriate?Answering these questions is a time consuming process, justifying the
plethora of published ready made pipelines each providing a polished
workflow for a typical study type or use case. The price for the
convenience of such a polished pipeline is the lack of flexibility -
they are not meant to be adapted or extended to match the needs of a
particular study. Workflow management systems on the other hand offer
great flexibility by focussing on the orchestration of user defined
workflows, but typicially require significant initial effort as they
come without predefined workflows.YMP strives to walk the middle ground between these. It brings
everything needed to classic metagenome and RNA-Seq workflows, yet
built on the workflow management systemSnakemake, it can be easily
expanded by simply adding Snakemake rules files. Designed around the
needs of processing primarily multi-omic NGS read data, it brings a
framework for handling read file meta data, provisioning reference
databases, and organizing rules into semantic stages.Working with the Github Development VersionInstalling from GitHubClone the repository:git clone  --recurse-submodules https://github.com/epruesse/ymp.gitOr, if your have github ssh keys set up:git clone --recurse-submodules git@github.com:epruesse/ymp.gitCreate and activate conda environment:conda env create -n ymp --file environment.yaml
source activate ympInstall YMP into conda environment:pip install -e .Verify that YMP works:source activate ymp
ymp --helpUpdating Development VersionUsually, all you need to do is a pull:git pull
git submodule update --recursive --remoteIf environments where updated, you may want to regenerate the local
installations and clean out environments no longer used to save disk
space:source activate ymp
ymp env update
ymp env clean
# alternatively, you can just delete existing envs and let YMP
# reinstall as needed:
# rm -rf ~/.ymp/conda*
conda clean -aIf you see errors before jobs are executed, the core requirements may
have changed. To update the YMP conda environment, enter the folder
where you installed YMP and run the following:source activate ymp
conda env update --file environment.yamlIf something changed insetup.py, a re-install may be necessary:source activate ymp
pip install -U -e .