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<p>As this needs to done on a case-by-case basis it has not been implemented by the UniverSC core functions. We provide this workaround for using published data and data already processed by sequencing facilities. Please contact the maintainers or file an issue on GitHub if you are having problems with this case.</p>
<h4id="custom-inputs">Custom inputs</h4>
<p>Custom inputs are also supported by giving the name "custom" and length of barcode and UMI separated by a "_" character.</p>
<p>Custom barcode files are also supported for preset technologies. These are particularly useful for well-based technologies to demutliplex based on the wells.</p>
<p>Note that custom inputs do not remove linker or adapter sequences for combinatorial indexng technologies. These must be removed from the Read 1 file before running UniverSC. To request a preset technology setting instead, please submit a feature request on GitHub as described below.</p>
<h2id="release">Release</h2>
<p>This tool will be released open-source (see <ahref="#licensing">legal stuff</a> below). We welcome any feedback on it and any contributions to improve it. Hopefully it will save people time by making it easier to compare technologies.</p>
<p>We have tested it on several technologies but we need users like you to let us know how we can improve it. We hope that it will save you time by handing tedious parts of data formatting so that you can focus on the results.</p>
<p>A submission to a journal and biorXiv is in progress. Please cite these when they are available. Currently, the package can be cited as follows:</p>
<p>Kelly, S.T., Battenberg, Hetherington, N.A., K., Hayashi, K., and Minoda, A. (2021) UniverSC: a flexible cross-platform single-cell data processing pipeline. bioRxiv 2021.01.19.427209; doi: <ahref="https://doi.org/10.1101/2021.01.19.427209"class="uri">https://doi.org/10.1101/2021.01.19.427209</a> package version 1.2.4. <ahref="https://github.com/minoda-lab/universc"class="uri">https://github.com/minoda-lab/universc</a></p>
<p>Please cite our publication when you use our software as follows:</p>
<p>Battenberg, K., Kelly, S.T., Ras, R.A., Hetherington, N.A., Hayashi, K., and Minoda, A. (2022) A flexible cross-platform single-cell data processing pipeline. Nat Commun 13, 6847 (2022). https://doi.org/10.1038/s41467-022-34681-z</p>
<pre><code>@Article{pmid36369450,
author="Battenberg, K. and Kelly, S. T. and Ras, R. A. and Hetherington, N. A. and Hayashi, M. and Minoda, A. ",
title="{{A} flexible cross-platform single-cell data processing pipeline}",
journal="Nat Commun",
year="2022",
volume="13",
number="1",
pages="6847",
month="Nov",
note = {https://github.com/minoda-lab/universc package version 1.2.4},
<p>Kelly, S.T., Battenberg, Hetherington, N.A., K., Hayashi, K., and Minoda, A. (2021) UniverSC: a flexible cross-platform single-cell data processing pipeline. bioRxiv 2021.01.19.427209; doi: <ahref="https://doi.org/10.1101/2021.01.19.427209">https://doi.org/10.1101/2021.01.19.427209</a> package version 1.2.4. <ahref="https://github.com/minoda-lab/universc">https://github.com/minoda-lab/universc</a></p>
<pre><code>@article {Kelly2021.01.19.427209,
author = {Kelly, S. Thomas and Battenberg, Kai and Hetherington, Nicola A. and Hayashi, Makoto and Minoda, Aki},
title = {{UniverSC}: a flexible cross-platform single-cell data processing pipeline},
<p>The software can also be cited directly as a manual:</p>
<pre><code>@Manual{,
title = {{UniverSC}: a flexible cross-platform single-cell data processing pipeline},
author = {S. Thomas Kelly, Kai Battenberg, Nicola A. Hetherington, Makoto Hayashi, and Aki Minoda},
@@ -410,7 +425,7 @@ docker run hello-world </code></pre>
<pre><code>docker run -it tomkellygenetics/universc:latest /bin/zsh </code></pre>
<p>Either of these shells are supported.</p>
<p>Note that Docker containers run with a default of 2 GB of memory. It is recommended to use at least 8 GB of memory as this is often insufficient for running UniverSC. Ideally, 16 GB of memory should be used if it is available on your system.</p>
<p><code>docker run --memory 16g -it tomkellygenetics/universc:latest /bin/bash</code></p>
<pre><code>docker run --memory 16g -it tomkellygenetics/universc:latest /bin/bash</code></pre>
<h5id="building-the-docker-image-locally">Building the Docker image locally</h5>
<p>The Dockerfile is provided in the repository so it can be built from source. This will build a Docker image with the latest version of universc provided that updates to dependencies on GitHub are still compatible.</p>
